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We are in the midst of a global crisis. The coronavirus, or COVID-19, has officially been declared a pandemic and it is wreaking havoc across the globe. Countries are getting shut down, economies are severely affected and the stock market is crashing to the ground.
Given that we now have a bit of time on our hands, I wanted to use this to understand if there’s a correlation between working from home and the spread of the coronavirus. As a member of the data scientist community, I go with logical quantitative estimates rather than qualitative estimates. This triggered me to do some research on this topic.
My aim here is to answer why we need to strictly follow social distancing to control the spread of Coronavirus with the support of available data.
I have analyzed the disease outbreak using the data hosted by John Hopkins University which is updated on an hourly basis. The data source contains three files – Total Confirmed Cases, Deaths and Recoveries. From this data (till March 22, 2023), I plotted how the cases grew over time from the starting day of outbreak i.e. from the day when the first case is reported.Here’s What We’ll Look At:
Top 10 Affected Countries
Current Coronavirus Situation in India
Is Social Distancing the Right Measure to Stop the Spread?
Learning From the 1918 Flu
Global Epidemic and Mobility Model (GLEAM) Estimate on China with Travel Ban
Estimating the Impact of Social Distancing in the US in the Coming Days
Model Virus Transmission with Social Distancing in the USTop 10 Affected Countries
The graphs clearly show how the outbreaks grew exponentially after crossing the ‘outbreak’ threshold. This triggers a strong signal to every country about the intensity of the situation. If not taken seriously, the coronavirus cases can compound quickly and the growth is almost exponential so even a small number of cases could balloon into a full-blown outbreak very fast.
For instance, Italy took 23 days to cross 100 cases and just 13 more days to cross 5000 cases and is now at 53,578. Likewise, the US seems to be following the same pattern. It took 41 days for the US to cross 100 cases and just took 14 days to cross 6000 cases and now stands at 25,489. Currently, the US appears to have an even worse trajectory than Italy.Current Coronavirus Situation in India
The world’s second-largest populated country India took 44 days to cross 100 cases and is now at over 400 cases. The virus spread growth post 100 days as compared to other top countries (in terms of virus transmission) in India seems to be in better shape.
Is it because of the early and serious implementation of social distance measures? India reported its first restriction of a travel ban on international arriving passengers starting from Mar 13, 2023, when it had 82 confirmed cases.
Is India not testing enough cases? Is that where we are missing the exact spread growth? The assumption is the disease has still not spread in the community. The country tested 826 samples collected from patients suffering from an acute respiratory disease from 50 government hospitals across India between 1 and 15 March.
Existing labs in India are able to provide results in six hours and each lab has the capacity to test 90 samples a day. The country is planning to increase its capacity to test 8,000 samples with the regular process and 1400 with rapid testing labs. So, to clearly analyze disease spread and model the Indian scenario, we need to wait for a couple of weeks.Is social distancing the right measure to stop the spread?
Preliminary analysis suggests that the key influencing factor for the rise in cases across the globe is disease spread. Those with the virus can unknowingly infect others before symptoms appear, some as soon as two days after infection. Patients are able to spread the infection until they recover.
According to the “Estimating the generation interval for COVID-19 based on symptom onset data” report, the proportion of pre-symptomatic transmission was 48% (95% CI 32-67%) for Singapore and 62% (95% CI 50-76%) for Tianjin, China.
There is one very simple thing we can do that works in reducing spread – social distancing. The idea is to reduce person-to-person contact in order to make spreading the disease less likely. This could ensure that there are sufficient resources available for a sick population, which in turn will help improve survival rates.Learnings from the 1918 Flu Pandemic
The below chart shows the impact of social distancing in 1918 for the flu in the US. For example, a city like St. Louis took measures 6 days before Pittsburgh and had less than half the deaths per citizen. On average, taking measures 20 days earlier halved the death rate:
SourceGlobal Epidemic and Mobility Model (GLEAM) Estimate on China with Travel Ban
The GLEAM model generates an ensemble of possible epidemic scenarios described by the:
Number of newly generated infections
Times of disease arrival in each subpopulation, and
Number of traveling infection carriers
The below chart shows the impact that the Wuhan travel ban had on delaying the epidemic. The bubble sizes show the number of daily cases. The top line shows the cases if nothing is done. The two other blocks show decreasing transmission rates. If the transmission rate goes down by 25% (through Social Distancing), it flattens the curve and delays the peak by a whole 14 weeks. Lower the transition rate by 50%, and you can’t see the epidemic even starting within a quarter.
There are many companies like Google, Microsoft, Verizon and others that are encouraging social distancing policies. As per this link, 790+ companies are currently encouraging social distancing.Impact of Social Distance on the US in the Coming Days – Statistical Simulation Estimate
Individual is able to become infected
Individual has been infected with a virus, but due to the virus incubation period, is not yet infectious
Individual is infected with a virus and is capable of transmitting the virus to others
Individual is either no longer infectious or “removed” from the population
In the SEIR model, the population is classified into one of the compartments mentioned in the above figure. Compartmental models are governed by a system of differential equations that track the population as a function of time, stratifying it into different groups based on risk or infection status.
The independent variable used in the model is time, measured in days. The dependent variable of interest is a fraction of the total population in each of the four compartments.
The data is simulated using the Euler method i.e. at any given point (t, y), the method will calculate dx/dt. The sequence of x-values like x0, x1, x2, x3 and so on are generated using this method. Starting from a given x0 and computing each rise as slope x run:
xn = xn-1 + slopen-1 Delta_t
where Delta_t is a suitably small step size in the time domain.
For the SEIR model, the dependent variables are s, e, I and r. Now, the four Eulers of the form:
SEIR models ordinal differential equations:
Here, N =S+E+I+R. N is a constraint that indicates there are no birth/migration effects in the model; the population is fixed from beginning to end.
For SIR equations, the final Euler formulas will be:
The following parameters are required to simulate the scenario:
Beta is the inverse of the incubation period (1/incubation days(5.2 days))
Alpha is the average contact (infection) rate in the population – 2.2
Gamma is the inverse of the mean infectious period (1/infectious days(2 days))
US Population: 331,002,651 (Mar 22, 2023 Estimate)
Model-Virus Transmission without Social Distancing in the US
Without social distancing, the base model suggests 18% of the US population will be infected with the disease after 40 days from the first exposure, which clearly triggers the warning signal.Model-Virus Transmission with Social Distance in the US
Adding ρ (encounter rate) to the model to capture the social distancing effect. The value of ρ ranges from 0 to 1, where 0 indicates everyone is locked down and quarantined while 1 is equivalent to our base case.
Considering a scenario of cutting the encounter rates by 50% (through social distancing policies) clearly shows the virus transmission in the above graph has come down to approximately 3%. We can generate different scenarios by modifying all configurable parameters like ρ, incubation period and other things.Final Thoughts
Coronavirus cases’ exponential growth shows us that we need to strictly follow social distancing measures to protect ourselves and others. Early signs presented in Graph 1 are showing that spread has come to control in China and South Korea. China experienced a period of exponential increases in COVID19 cases but that seems to be leveled out.
China started taking severe restrictive lockdowns and quarantines on its cities starting from Jan 23, 2023. Despite these extreme measures, it took almost about 30 days and an additional 80,000 cases before the curve flattened out. That’s the cost of delaying or not following social distance measures.About the Author
Bala Gangadhara Thilak Adiboina
I am currently working as a data scientist with a leading US Telecom Company. I am a hardcore data science guy who loves to solve every problem using data science. I am currently pursuing my Ph.D. from IIM Ranchi in the data science space.
You're reading Coronavirus Analysis: Will Social Distancing Help Prevent The Spread?
For as long as humans have been alive, we’ve been memorializing, praying, and ritualizing the significant turns of life, and death. Even Neanderthals might have buried their dead. Across the world today, saying farewell to a beloved family member could mean anything from Malagasy turning of the bones ceremonies to Jewish communities sitting shiva.
“It’s pretty much written into our DNA as humans as much as language [is],” says Maribel Alvarez, an anthropologist at the University of Arizona.
The main thing that these rituals have in common is community. Right now, when people are more separated than ever, it can feel impossible to properly mourn the loss of human life to COVID-19 or anything else.
Losing someone you love is always awful, but amidst a global pandemic, it almost seems unrecognizable. People are dying alone in hospitals from a virus that is still baffling doctors, health officials, and other experts. Just as troubling for the world over is how to deal with the loss of a loved one at a time when staying apart is imperative.
The first step to dealing with grief while isolated is to understand what you’re feeling, says Kathy Shear, the founder and director of the Center for Complicated Grief at Columbia University. Grief isn’t synonymous with feeling down or struggling with depression; the condition is marked by yearning, longing, and sadness as the result of losing someone, or something, we value, and coming to terms with a less-than-ideal reality.
“Grief is the response to losing something or someone very meaningful to us,” Shear says. “Each relationship we lose, we experience grief in a different way because it really depends on what we lost.”
Guilt and anger can also accompany sadness and longing, and further boggle your mind with what if’s. This can be especially heightened as people die without their family near them, or if certain members of a household succumb to the virus, and others survive.
It’s this lingering guilt and anger that sometimes latches on to our lives, making grief something harder to overcome, Shear says. Often, feeling shame or guilt because of how a loved one dies makes it feel like you need to be in pain all the time, making it hard to find peace with reality.
On the other hand, if you’re at home trying to work, raise children, and keep your life under control during the pandemic, all of this can also make it hard to take a moment and really let the grief set in. Shear says it’s okay to postpone your pain if that is what feels best to get through this unprecedented time.
“That’s kind of okay,” she says. “People need to give themselves permission for however way they manage.”
No matter what, it’s important to maintain your wellbeing and ability to be happy, Shear adds. And if your grief, or any other negative emotions, start to overpower your life, you should open up to a friend, mentor, or even a professional that can be accessed without breaking social isolation.
It’s also important to know that even if you haven’t lost someone you love recently, you can still grieve. We’ve all lost freedom and familiarity, some of us have lost jobs, or canceled weddings and graduation ceremonies.
“Sometimes I think it truly is grief,” Shear says of these kinds of emotions. “One of the tip-offs that it is grief is the yearning for something.”
People are social, and we simply don’t grieve well on our own, Shear says. When someone dies, a funeral isn’t just for the sake of reciting scripture passages and breaking out all-black ensembles. Grief is a jarring experience, one that can take over your life. Being with other people who are sharing the experience can feel like a safety net catching you before you hit rocky ground.
“[Social distancing] does take away the opportunity to collectively share,” the University of Arizona’s Alvarez says, “and in that sharing and marking of time, in those memorials where we cry together and sing together, [we really are providing] a soft landing for these very harsh emotions.”
So, what can people do if you can’t process grief in a social way? Alvarez suggests looking not so much at what a ritual is on the surface, but what it provides.
We don’t go to weddings, graduations or funerals over and over again because we need to learn something. But we still show up. And the reason is simple — sometimes, we need to sit there and recognize the change that is happening in our lives and the world around us.
“The essence of ritual is yes being in collectivity with others, but it’s also making it really thick and pausing in the moments to bring certain reflections,” Alvarez says. “I don’t think the opportunity to do that is gone.”
What we can do, Alvarez says, is provide that time for reflection, and add it into our daily lives in the things we are allowed to do.
“We can embellish something that is ordinary,” she says. “A day where you cut flowers and put them on the table and light candles and sing songs. Or bring out photographs. None of these activities we are prevented from doing.”
If you think about it, people have been doing these kinds of nontraditional rituals since before COVID-19, like an online bulletin board that can be accessed by people all across the world or motorcyclists driving together in honor of deceased people, Alvarez adds. Actions that seemed to be oddities before could be the thing you need to help cope with grief you feel now.
While it might seem like the time to despair, it can be a time to get creative, Alvarez adds. Make your daily neighborhood walk into a reflection on the loss of someone you love, and allow yourself to make everyday actions into a ceremony of their own to come to grips with all of the complex emotions that grief brings. A ceremony isn’t necessarily a ceremony because of what you wear, do, or say—it’s about allowing yourself to accept change and all the emotions that come along with it.
Even during typical circumstances, almost every social media channel is booby-trapped with misinformation. Companies have regular methods in place to try to mitigate the phenomenon, but the coronavirus has proved particularly challenging. It’s a global event with rapidly changing developments and statistics that require constant vetting and evaluation. When misinformation slips through the cracks, the results can be particularly and immediately harmful.
Many tech companies already have systems in place to try to combat misinformation, but have ramped up their efforts in light of the coronavirus. Here’s an overview of what some of the biggest players in social media are doing to stick to the facts.Facebook
On March 18th, Facebook launched its Coronavirus Information Center, which acts as a hub to collect updates and content directly from sources such as the World Health Organization as well as other trusted media outlets. When users follow the Coronavirus Information Center, they receive notifications about new content or important updates.
The majority of Facebook users, however, aren’t getting their coronavirus information from Facebook’s hub. Fraudulent posts pop up in every corner of the service from the newsfeed to private groups that are totally unrelated to the virus. That falls more to the company’s more general misinformation guidelines. Here are the parameters laid out in Facebook’s coronavirus guidance: “Since January, we’ve applied this policy to misinformation about COVID-19 to remove posts that make false claims about cures, treatments, the availability of essential services or the location and severity of the outbreak. We regularly update the claims that we remove based on guidance from the WHO and other health authorities.”
For content like conspiracy theories, the company relies on its regular network of roughly 55 fact-checking organizations to evaluate its merit. If something is deemed inaccurate or misleading, fewer users see it and it’s accompanied by an alert or pop-up to suggest its possible inaccuracy.
While Facebook tries to automatically intercept this kind of misleading message before it reaches many people, the approach’s efficacy has limits. Content shared within private groups can still regularly slide under the radar, which is why you might see more bad coronavirus info popping up in places like garage sale communities or other groups. You should still report them when you see them to flag them for the company’s attention. But, with increased volume, Facebook says it’s prioritizing content that could cause harm or directly dissuade people from getting treatment, so there may be a delay in reviewing reports.
If your content gets flagged, you can still appeal its removal, and Facebook will take note of your disagreement, but likely won’t review it again for a chance at reinstatement due to the sheer volume of reports and its available staffing.WhatsApp
While the encrypted messaging service is part of Facebook, it has a few specific tweaks. Earlier this week, WhatsApp announced that it would expand its program to limit forwarded messages to stop bad info from going viral. The app has been labeling messages with many forwards with a double arrow icon to clearly show users that the information didn’t come from a close contact. Now, users can only forward this kind of content to one chat at a time rather than spamming it out to their entire list of contacts.
WhatsApp is also asking users to forward potentially misleading or harmful information spreading on its service to flag it for review. Like Facebook proper, WhatsApp relies on a selection of fact checkers to evaluate posts. The high volume will likely affect response times.
Some reports peg WhatsApp as particularly fertile ground for coronavirus misinformation. Even the Irish Prime Minister Leo Varadkar tweeted to urge people not to share “unverified info on WhatsApp groups.”Twitter
Twitter typically relies on automated systems to evaluate the information in tweets, but it’s ramping up its AI efforts during the coronavirus pandemic. As the service receives more reports with its workers spread out in remote offices, Twitter says it’s increasing its automated efforts to try to identify misleading content before users report it. There’s an element of mystery to these efforts, but we do know, however, that Twitter will not permanently suspend users based purely on judgement calls made automatically without a human evaluation.
According to Twitter, users should continue to report misleading content, but should expect a longer delay between report and response due to the increased volume. Coronavirus-related posts will still go through human teams, whether they’re kicked up by AI or human users.YouTube
YouTube’s coronavirus warning is relatively subtle compared to some other services.
YouTube’s biggest coronavirus issue landed this week when a popular livestream with 65,000 viewers falsely claimed that there’s a link between 5G wireless networks and the spread of COVID-19. The speaker also failed to condemn incidents in the UK in which people had set fire to 5G towers based on that conspiracy. YouTube deleted the video after it had finished, but the event exposed a particularly tricky position for the video behemoth.
The 5G conspiracy content reportedly falls under what YouTube considers “borderline content.” It doesn’t directly influence people to take harmful actions or dissuade them from seeking treatment, but it’s unfounded and, in this case, simply false. Now, YouTube is directly restricting the reach for videos promoting the 5G conspiracy on top of its normal practices.
In normal usage, searches for coronavirus topics result in a notification at the top of the page guiding viewers to the CDC’s official website when you’re in the US. Other countries may produce different alerts guiding them to services like the NHS or the most appropriate source in their home country.Google
Google presents users with a full-on information hub regarding coronavirus. Alphabet
Search Google for “coronavirus” and you’ll arrive at a curated content hub filled with trusted sources and confirmed statistics as well as direct links to health organizations. The hub also promotes local and health authorities across other social media platforms like Twitter, and a section called “common questions,” with immediate answers to some of the most popular queries.Pinterest
Last year, Pinterest took a strong stance against misinformation regarding vaccines. Searching for any terms relating to “anti-vax” directs users to official sources of information like the WHO. The company has taken a similarly hard line against misinformation regarding coronavirus. Searching for “coronavirus” now brings up messages as well as a grid made almost exclusively of informational graphics from reputable sources.
Even searching for terms like “coronavirus masks,” which would typically be right in the service’s DIY wheelhouse, turns up the same results.
Sentiment analysis tools will help you evaluate the attitudes of your target consumers — attitudes that can make or break your brand’s reputation.
How do people feel about your brand — right now? This question may seem basic. But it can be critically important for marketers, as it should inform every aspect of your content and marketing strategies.
Social media sentiment analysis gives brands an opportunity to track online conversations about themselves and their competitors in real time. At the same time, they gain quantifiable insights about how positively or negatively they are viewed.
Social media sentiment analysis makes sure you know how every brand choice affects brand loyalty and customer perception.
It may sound complex. But there are plenty of tools to help you gather and analyze the social data you need to understand exactly where your brand stands.
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What is social media sentiment analysis?
Social media sentiment analysis is sometimes called “opinion mining.” That’s because it’s all about digging into the words and context of social posts to understand the opinions they reveal.
Measuring social sentiment is an important part of any social media monitoring plan.
How to run a social media sentiment analysis in 3 steps
In the section below, we get into some powerful tools you can use to help make social sentiment analysis faster, easier, and more accurate.
But if you’re not yet ready to invest in specialized social media sentiment analysis tools, you can get started with a bit of extra research.1. Monitor your mentions
The first step of social media sentiment analysis is to find the conversations people are having about your brand online. The challenge is that they won’t always tag you in those conversations.
Fortunately, you can set up Hootsuite streams to monitor social channels for all mentions of your brand, even when you’re not tagged. Here’s how to collect them all in one place.
In the Hootsuite dashboard, add a stream for each of your social accounts. This will track the mentions where people tag your accounts on social.
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You might want to organize all of your Mentions streams into a Social Mentions board to make them easier to view at a glance.
On some social media platforms, you can even track the posts where you’re not tagged:
For Instagram, you can monitor hashtags related to your products or brand name.
For Twitter, you can use hashtags or keywords.
Be sure to create streams for your brand name and your product or service names.
Again, a board can be a helpful way to organize all of these streams on one screen.
For more details on getting set up to track your mentions, check out our full post on social listening tools.2. Analyze the sentiment in your mentions
Next, you’ll look for terms that indicate sentiment within your mentions. Think about the kinds of positive or negative words people might use to talk about your brand. Examples might include:
Positive: love, amazing, great, best, perfect
Negative: bad, awful, terrible, worst, hate
There will likely be other terms specific to your product, brand, or industry. Make a list of positive and negative words and scan your mentions for posts that include these terms.
For Twitter, you can set Hootsuite up to do some of this work automatically. In the dashboard, create a search stream using your name plus 🙂 to indicate positive sentiment. Then create a search stream using your name plus 🙁 to indicate negative sentiment.
If you’re tracking sentiment manually, keep in mind that you need to watch out for the context. Is someone being sarcastic when they say they had “the best” customer experience with your brand?3. Calculate your social sentiment score
You can calculate your social sentiment score in a couple of ways:
Positive mentions as a percentage of total mentions
Positive mentions as a percentage of mentions that include sentiment (removing neutral mentions)
Which method you use doesn’t really matter, as long as you are consistent. That’s because the most important thing to watch for is change.
The second method will always result in a higher score.
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As we just said, Hootsuite is a powerful tool for collecting the data you need for sentiment analysis. These tools take things a step further by providing that analysis for you.
Hootsuite Insights powered by Brandwatch allows you to use detailed Boolean search strings to monitor social sentiment automatically. You’ll also get word clouds showing the most common words used to talk about your brand. Plus, charts that benchmark your social sentiment against your competitors.
In addition to positive and negative sentiment, Hootsuite Insights tracks specific emotions, like anger and joy, over time. This allows you to look for sudden changes, or ongoing trends. You can also filter sentiment by location or demographics, so you can see how sentiment varies across your audience. There’s also an AI analysis option to automatically identify the causes of significant changes in sentiment.
Alerts are another handy feature that allow you to be notified if there’s a sudden change in sentiment. Then you can get ahead of any issues before they get out of control.
Mentionlytics’s pitch is: “Discover everything that is being said about your brand, your competitors or any keyword.”
You can broaden the scope of your search to see what people are saying about your brand all over the internet. There’s a built-in sentiment analysis feature that works in multiple languages.
Digimind identifies and analyzes all the relevant conversations about your brand and competitors.
It pulls information from more than 850 million web sources, so you know you’re getting a comprehensive view of sentiment toward your brand.
You can also analyze mentions and apply filters to highly customize your sentiment analysis process.
Crowd Analyzer is an Arabic-language social listening and sentiment analysis tool. This is especially important for brands with an Arabic-speaking target audience. Other social sentiment tools do not generally have the capability to recognize sentiment in Arabic posts.
Source: Hootsuite App Directory
TalkWalker gathers information from more than 150 million sources. The tool then uses artificial intelligence to analyze sentiment, tone, emotions and much more.
Bonus: Free social media sentiment report template
Our social media sentiment report template provides the structure you need to create an impactful report to share with your team.
Bonus: Get a free social media sentiment report template to easily track audience sentiment over time.
3 ways to improve your brand sentiment on social media
The benefits of tracking social media sentiment are a little bit circular. For example, tracking social sentiment helps you better understand your audience, which in turn helps you improve social sentiment.
So, if you were paying attention to the benefits section above, these strategies might sound a little familiar…
Know your audience: When you know your audience well, you can craft messaging that connects with them. Basically, it boils down to this: Give your audience more of what they want and less of what they don’t.
Play to your strengths: Use social sentiment to understand what your audience thinks is great about your brand — and what they think is not so hot. While you work on improving the lagging areas, play up your strengths. Provide value while remaining true to your brand identity.
Why is social media sentiment analysis so important?
A simple tally of your social mentions only tells you how much people are talking about your brand online. But what are they saying? Social media sentiment analysis helps you answer this question.
After all, a high number of mentions might look great at first glance. But if it’s a storm of negative posts, it might not be so great after all.
In July, BMW’s social mentions spiked — but the engagement was not positive. Confusion ran rampant about a planned decision to sell subscription services for in-car functions. The Tweet that really set things off got nearly 30,000 retweets and 225,000 likes.
This is wild — BMW is now selling a monthly subscription service for heated seats in your car.
The car will come with all the necessary components, but payment is needed to remove a software block.
Welcome to microtransaction hell.
— Joe Pompliano (@JoePompliano) July 12, 2023
If the company had just been counting mentions, they could have thought they’d done something very right.
But the sentiment behind this increased activity was primarily negative. BMW was forced to clarify its subscription plans.
Let’s talk heated seats… ⤵️
— BMW USA (@BMWUSA) July 14, 2023
Here’s why your brand needs to track social sentiment.1. Understand your audience
Marketers do their best work when they understand their audience. That means you need to understand how your audience feels about your brand, your social posts, and your campaigns, not just how much they mention you.
For example, White Castle used social listening and sentiment analysis to discover that their customers have a positive association with the very specific experience of eating White Castle sliders while watching TV in bed.
With this knowledge in hand, White Castle featured a couple eating sliders in bed in their next campaign.
Source: White Castle ad via eMarketer Industry Voices
Ongoing social media sentiment analysis can also alert you quickly when customer preferences and desires change.2. Improve customer service
Monitoring sentiment provides two major benefits for customer service and support:
It can alert your teams to any new or emerging issues. You may even learn about issues with a particular product run or product. You can then prepare your team, or even create social content that addresses issues directly.
You can proactively reach out to people who may be having a challenging experience with your brand. A simple response or follow-up can often go a long way to resolve a customer issue before they even contact your team.
In this example, Adobe’s Twitter customer support team was able to resolve an issue and leave the customer happy even though they were not tagged.
Feel free to reach out whenever needed. Thanks. ^RS
— Adobe Care (@AdobeCare) September 26, 20233. Tweak brand messaging and product development
By following trends and investigating spikes in positive, negative, or neutral sentiment, you can learn what your audience really wants. This can give you a clearer idea of what kind of messaging you should post on each social network.
You may even gain insights that can impact your overall brand strategy and product development.
For example, Zoom monitored their social sentiment to uncover the biggest negative myths about their product. They then created a series of TikTok videos to bust those myths, improving customer confidence.
They also created a series of “Pro Tips” videos to answer the most commonly asked questions on social, thereby reducing the workload for the customer service team, while highlighting new features. Some of the ideas for new features even came from social listening and analysis.4. Understand where you stand in your niche
Brands cannot be all things to all people. Social sentiment can help you understand where you stand in your business niche. This, in turn, can help you reach the right audiences with the right messages at the right time.
For example, the production team at the media company Underknown launched a YouTube channel called “According to Science.” They told stories based on scientific research. But after 60 videos, the channel wasn’t growing.
After analyzing their data, the team realized that videos focused on survival got the most positive response. They tweaked their entire strategy and launched a new channel called “How to Survive.” The channel gained a million YouTube subscribers in only 18 months.
When they discovered their most positive responses came from Americans aged 18 to 34, they further adapted by creating short videos that live on TikTok and regularly get more than a million views.
Social media sentiment analysis can also help you understand in which areas of your business you really excel, and what you might need to improve.5. Spot brand crises early
You never want your brand to fall into a crisis. But if it happens, monitoring social sentiment can help you spot the problem early. You can implement your crisis response plan to minimize negative sentiment or avoid it entirely.
In the BMW example above, the car company took 48 hours to reply to the heated seats controversy on Twitter, and another day to get an official statement up on its website. By then, the issue had gained significant media coverage, making it harder for BMW to undo the damage. Had they responded within the day, they might have been able to correct the narrative before it got out of control.
Setting up automatic alerts for spikes in mentions and sentiment is an important early-warning system for brand crisis management.
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Is social media getting you down? Maybe you have a good presence there, but things just aren’t hot yet?
Don’t worry, this is something a lot of businesses go through.
One fantastic way to make a bigger impact and start to see awesome engagement is to make sure your social media content is on point. After all, your audience is human, and they’re reading (scanning) your content, right?15 Tips to Write Killer Content for Social Media
Here are my top tips to help you put your best foot forward on social media with your written content.
I’ll break them down per social platform, starting with Twitter.3 Must Have Twitter for Business Tips
You’re on Twitter, but what are some must have tips that can help you write better Twitter content? Here are a few to take with you as you tweet.
1. Add Images to Your Tweets for Maximum Interaction
Your content might be awesome, but if you don’t add images, you’re going to lose out major on engagement and interaction.
Example of Buffer tweet + image:
— Buffer (@buffer) September 25, 2023
2. Understand the Difference Between Your Voice and Tone
Writing the right content means you also need to know the difference between what voice and tone mean. You need to have a consistent voice throughout your social media usage, but when it comes to the different channels, different tones can work. On Linkedin posts, for example, your tone may need to be a bit more serious. With Twitter, your tone should be more conversational and fun. Don’t change your voice, but change up your tone. Take a look at these two radically different “tones” from the awesome Mailchimp:
Tweet 1: Serious
— MailChimp (@MailChimp) September 24, 2023
Tweet 2: Fun
Don’t change your voice. Listen to your mother and change your tone to see some awesome results.
3. Write Tweets that are Perfectly Conversational
Keep things chatty (meaning conversational, not long) when you’re writing for Twitter. It is more of a laid back channel, which means keeping things in a conversational tone will help you bring about more engagement.Three Awesome Tips for Writing Excellent, Engaging Facebook Content
Now, what about Facebook content? How can you get something that is outstanding and engaging?
4. Find and Use the Perfect Recipe for a Facebook Post
The first step to creating great Facebook content is to learn the perfect recipe for a post. Kevan Lee from Buffer gives an excellent recipe that can really help your social content be the best possible. He says that a great Facebook post:
Should be an actual link
Is brief (fewer than 40 chars)
Is published at times that aren’t peak
Is part of a regular content creation schedule
Is newsworthy and timely
And remember; don’t fear mixing it up a bit to find your own recipe that works for your brand.
5. Use Your Visuals on Facebook to Drive More Engagement
Visuals really are a huge part of social media content, no matter the channel. And Facebook visuals are a great way to have better content. Photos on Facebook get seven times the amount of likes, and 10 times the number of shares over content that only links to a page or is just written content. You can add text on photos, create collages, and use your images to break up all of the written content out there on Facebook. And remember, make sure your profile and cover photos are perfect to represent your brand while also helping you stand out.
6. Prepare to Write Some Excellent Long-Form Facebook Content
Get prepared to get a new angle on Facebook content. Instead of just making a simple little post, you will soon be able to write long form content. This is really going to help amp up your Facebook content game, and get you the engagement you are looking for on social media.3 Excellent Ways to Use LinkedIn to Reach Out
LinkedIn is a great way to connect with other industry insiders and leaders, but how can you get great social media content on LinkedIn? Take a few of these tips with you.
7. Keep Your LinkedIn Audience in Mind, Crafting Perfect Content
LinkedIn has a specific audience and you need to know how to write for that audience. When you are writing LinkedIn content, make sure you are writing for that demographic, which is more professional. Write posts that you only post on LinkedIn and no other place.
8. LinkedIn Pieces Do Better When They are Shorter
The short versus long content debate is constantly raging on. And, while longer content does tend to prove to be the best bet for most blogs when it comes to LinkedIn, shorter is better. Since you are reaching a more business-oriented audience, you want to give them something easy and quick to read. Help make it easy for them to read your blogs by creating shorter pieces. Fellow SEJ contributor Amanda DilSilvestro suggests keeping your posts no longer than 800 words.
9. Post Throughout the Week, but Don’t Over Post
Keeping to a consistent posting schedule is also a great way to improve your LinkedIn content and the engagement you receive. When it comes to posting on LinkedIn, you should be doing so during the work week, Monday through Friday, to give your readers the chance to read your content. You can spend all the time you want to on your content, but if you don’t post it at the right time, it’ll be completely overlooked.3 Stellar Tips that Can Help Improve Your Instagram Presence
Instagram is a great channel when it comes to using your visuals and adding personality to your brand. But how can you improve your content? Let’s take a look!
10. Make Sure Your Images are High Quality and Visually Appealing
The first step to great content on Instagram is to make sure your photographs are all high quality. This is the most important one. Your smartphone is an incredible camera already; you can easily take some time to practice your photography skills and get some excellent shots. Or, you can get some really awesome equipment, and take a killer shot—like @ocean did (theirs got a whopping 6,000+ likes):
11. Interact With Others and You’ll Grow Your Following
Instagram is also about the interaction, and if you start browsing your favorite hashtags, you get the chance to interact and grow your following.
Margot da Cunha from Wordstream suggests following your followers and also seeking out people you’d like to give your brand a follow. Once you find them, then it is time to start interacting and building a relationship.
12. Use Those Hashtags
While other social channels need less or no hashtags to improve engagement, Instagram still benefits quite a bit from them. In fact, Instagram posts from users with fewer than 1,000 followers get more traction if they have 11 hashtags.
I’d limit your usage to 10-15 hashtags per post. Don’t worry about loading up on the right ones. chúng tôi is a great tool to see how popular a certain hashtag is, and what tags might be similar.
With an Instagram only a couple months old, we saw good traction on this post when we used a few top hashtags, like #instablogger:3 Tips to Amp up Your Pinterest Game
Another great channel that is quickly on the rise for all sorts of businesses is Pinterest. Creating content for it is incredibly fun and here are a few things you should keep in mind to make the most of it.
13. Don’t Make Your Marketing Obvious, Make it Fun
When it comes to Pinterest, users don’t want to hear your sales speech.
Lauren Brousell from Cio says that you should leave the logos behind when it comes to your pins. And, if you do want to use your logos, make sure you put them on your own original photos and make them as subtle as possible.
You should link to things on your site, but you should also link to other websites and content to create a great variety of content for your users.
14. Share Fun, Relevant Gifs
Gifs are a huge part of the Internet right now, and you can easily incorporate gifs into your Pinterest strategy. Like this one.
You can create your very own gif board to share hilarious, fun, and relevant gifs or use relevant gifs that link back to your website. This is sure to help you stand out.
15. Create a Handful of Awesome Boards
Don’t go overboard when you create your boards. It is easy to create several boards, but you will want to stay away from creating too many.
Instead, brainstorm a handful of really great ideas and make your boards the best they can be.
As you pin to them, you can organize your pins, making it incredibly impactful. This will encourage people to follow you and keep an eye out for the things you pin.These Tips Can Help You on the Way to Social Media Greatness
This article was published as a part of the Data Science BlogathonIntroduction
According to Haines and Crounch, mathematical modelling is a process in which real-life situations and relations in these situations are expressed by using mathematics. In simpler terminologies, mathematical modelling is the process of describing systems (activities) with mathematics. Mathematical modelling is the process of using mathematics to model real-world processes and occurrences.
Mathematical modelling is used virtually in every sector, in the manufacturing industry mathematical modelling is used to model heat and mass transfer of fluids flow, the transformation of materials, e.t.c. The construction industry is not spared from the beauty of mathematical modelling, mathematical modelling is used to optimize the amount of port in structures, calculating the stress that will be imposed on buildings and how to counterbalance it. You probably must have seen the tallest building in the world either virtually or physically, you will be in awe if you were to see all the mathematical models that were used to model the building.
Burj Khalifa (Tallest Building in the world). Source
Football athletes use mathematical modelling to score goals, for football lovers you probably must have seen how Messi, Rolando, and other popular footballers use free kicks to score goals. The free-kick goals can be modelled with mathematics, by modelling the angle of trajectory, the drag e.t.c.
Modelling free-kick with Mathematics. Source
The astronomy industry heavily relies on mathematical modelling, mathematics is used to model the movement of spacecraft and other orbital objects. Katherine Johnson, a former mathematician at NASA used her mathematical prowess to help put an astronaut into orbit around the earth. Her mathematical skills were also used to deploy a man on the moon.
Photos of Katherine Johnson. Source
I can continue to list the sacrosanct role of mathematics in our world, but because of time constraints, I will stop here. The reality is that the world can exist without the English Language but the world can’t exist without Mathematics.
This article will walk you through the processes of modelling disease spread with mathematical models. You might be wondering can mathematics really model disease spread? The answer is yes, mathematics is very important in the health sector. According to TheConversation “Mathematical models are used to create a simplified representation of infection spread in a population and to understand how an infection may progress in the future. These predictions can help us effectively use public health resources such as hospital space or a vaccination programme. For example, knowing how many people in a population are likely to become infected can tell hospitals how much space and resources they will need to allocate for treatment.” Source
What it takes to mathematically model any disease
At the beginning of an epidemic, there exist, people who will be infected, prone to getting infected and those who might recover from the disease or die as a result of the disease. Those who were initially prone to the disease will get infected if they come in contact with infected people and those who will die will originate from the infected people. Mathematicians have been trying to successfully find a way to mathematically model the relationship between those who are prone to be infected, those who are infected and those who will recover from the disease. In 1927, Kermack & McKendrick came up with what is called the Susceptible, Infected and Recovered (SIR) Mathematical model. The SIR model assumes that for any given disease, there exist 3 categories of people those who are Susceptible (Prone to contracting the disease but are yet to be infected), those who are Infected and those who have been Removed(recovered) (either by death or with the aid of drugs). The SIR model has been of help to mathematicians and has made modelling disease spread easy.
To mathematically model any disease using the SIR model, you will need to assume that the population remains constant i.e ( No birth takes place, nobody migrates into the population, no natural death ( with an exception of death from the disease)). The SIR model models diseases by taking into cognizance that, the movement of people from the Susceptible into the Infected state and from the Infected State into the Removed state is defined by some constants. These constants are the tripod that the SIR model sits on, and that is what will be discussed soonest. You will agree with me that, for any disease to spread there must be contact between susceptible people and infected people or person( disease carriers).
Assuming for a particular epidemic, there exist 1000 Susceptible people and 3 persons that are infected. Take, for instance, every day 1 person gets infected due to the contact between Susceptible and Infected people. You will agree with me that, on the fifth day, 8 people will be infected and the number of susceptible will be 995. We might want to assume that 2 persons or 3 persons get infected, one thing here is that we are just making assumptions that might not be mathematically accurate. Hence the need to use the SIR model to mathematically and accurately model the spread of the disease.
The SIR model models the number of people who are infected by assuming that everyone in the susceptible category has an equal probability of being infected by a constant fraction which is called the contact rate (infection rate). The number of people that are infected is computed by multiplying the contact rate with the number of infected people and the Susceptible after which the population number is used to divide the result i.e (contact rate * S * I)/N. S-Susceptible, I– Infected, and N– Total Population Number. The contact rate will be a fraction of the population which is computed by analyzing the number of contacts made with infected people per day. The SIR model also models the number of people who will be removed by a certain fraction which is called the recovery rate. The number of people that will be removed is computed by multiplying the recovery rate with the number of infected people i.e recovery rate * infected people.
SIR Mathematical Model Source
ds/dt = the rate of change of the susceptible over time
dI/dt is the rate of change of infected over time
dR/dt is the rate of change of removed over time
The equation simply states that susceptible people will be reduced over time based on the contact rate (beta), the number of susceptible, the number of infected, and the total population (N). You will notice the presence of the negative sign, this is to show the fraction of people that will be lost from the susceptible category. The fraction of people that are lost from the susceptible category will be added to the infected category, hence the presence of the positive sign in the infected equation. Recall that the removed people originate from the infected category and the number of people that are removed is based on the removal rate multiplied by the number of infected people (gamma * I). Those that are removed will be a loss to the infected people hence the need to subtract the number of removed from the number of infected. The removed people will be gain to the removed category, hence the positive sign for the removed category.
Multiplying both sides with dt will give
dS is the rate of change i.e the difference between the old susceptible and the new susceptible ( Snew– Sold). The number of susceptible, infected, and Recovered for the next day can be modeled by moving the old Susceptible, Infected, and Recovered numbers to the other side of the equation to give.
SIR Model. Image by Author
The above equation can be used to model the number of susceptible, infected, and recovered for the next day. The number of infected people in a day depends on the contact rate(Beta) and the recovery rate (gamma).Other Types of Mathematical Models Used to Model Diseases
Apart from the SIR model, several varieties of mathematical models can be used to model diseases. Other models that were derived from the SIR models are the SEIR model, SIRV model, SIRD model e.t.c. The SEIR model models disease based on four-category which are the Susceptible, Exposed (Susceptible people that are exposed to infected people), Infected, and Recovered(Removed). The Susceptible, Infected, Recovered(Removed) and Vaccinated(SIRV) is another type of mathematical model that can be used to model diseases. The focus of this article is on the SIRD or SIID model which is Susceptible, Infected, Removed(Recovered with immunity), and Dead or Susceptible, Infected, Immune, and Dead model.
The SIID or SIRD model is an extension of an addition of two assumptions which are recovery with immunity and Death. For the rest of this article, I will interchange SIRD for SIID, both refer to the same acronym.
SIRD Model. Source
You will notice that the difference between the SIR and the SIRD model is the addition of the dD/dt which is the death rate per time. The SIID model models the death rate by considering a constant called the mortality rate(mu), which is the rate at which infected people die. The number of people who are dead is based on the product of the mortality rate with the number of Infected people. You will agree with me that the number of people who were infected and died must be removed from the number of infected people. If we remove the number of dead people, then our rate of change of infection over time will be modified to accommodate the loss due to death, which will give this.
SIRD image showing the mortality rate. Image by chúng tôi that is coloured with yellow is the mortality rate.Simulating Diseases with SIRD(SIID) (Practical)
Given the above information that immunity exists and people die as a result of the disease, it means we will use the SIID model to model the disease. Let’s assume the number of people who are infected by the disease is 3, the number of dead and recovered is zero, the infection rate(beta) is 0.5, the recovery rate(gamma) is 0.035 and the death rate(mu) is 0.005. Note that the infection rate, recovery rate, and death rate were gotten from here, but you can try any number.
SIRD Model modified from SIR. Image by Author.
The Susceptible number for the next day can be computed by using this method
Snew = Sold – (beta * Sold* Iold )/N
Sold = N – Iold = 1000-3 = 997 (i.e the susceptible number for the current day is the difference between the total population and the number of infected people in the current day)
beta = 0.5
Iold = 3
N = 1000 (The total Population)
Snew = 997 – (0.5 * 997 *3 )/1000
Snew = 997 – 1.4955
Snew = 995.5045
The total number of Susceptible for the next day is approximately 995.5
Let us compute the rest, the next day number of infected can be computed with this method
Inew = Iold + (((beta * Sold * Iold)/N) – (gamma * Iold) – (mu * Iold))
gamma ( recovery rate) = 0.035
mu (death rate) = 0.005
Inew = 3 + ((0.5 * 997 * 3)/1000) – (0.035 * 3) – (0.005 * 3))
Inew = 3 + (1.4955 – 0.105 – 0.015)
Inew = 3 + 1.3755
Inew = 4.3755
The number of people that will be infected the next day is approximately 4.4
Modeling the number of people that would have recovered with immunity the next day, that can be modelled with this equation.
Rnew = Rold + gamma * Iold
Rold = 0
Rnew = 0 + 0.035 * 3
Rnew = 0 + 0.105
Rnew = 0.105
The number of people who would have recovered with immunity the next day is approximately 0.11
Lastly, modelling the number of people who would be dead the next day, this method can be used which is the application of the last equation
Dnew = Dold + mu * Iold
Dold = 0 + 0.005 *3
Dold = 0 + 0.015
Dold = 0.015
These steps can be repeated to model the number of susceptible, infected, recovered and dead for the next 2 days and more days. What if the steps can be automated, instead of manually computing the numbers. Python Programming language will be used to automate the process and plot the result.Modelling Disease with Python Programming Prerequisites
To follow along, you will need to have python and preferably Jupyter notebook installed on your system. You can use this link to download anaconda, anaconda comes with a Jupyter notebook and python. You can use this video to familiarize yourself with the Jupyter notebook and how to install it.
Now that you have Jupyter notebook installed, you are good to go. Let us fire down# importing neccessary libraries import matplotlib.pyplot as plt %matplotlib inline # defining the variables total_population = 1000 total_infected = 3 total_susceptible = total_population - total_infected total_recovered = 0 total_dead = 0 # Number of days to simulate disease simulation_days = 500 # list to store the numbers of recovered people with immunity over time # the first element will be the initial number of people that has recovered with immunity recovered_list = [total_recovered] #list to store the number of dead people over time dead_list = [total_dead] infected_list = [total_infected] susceptible_list = [total_population] infection_rate = 0.5 recovery_rate = 0.035 death_rate = 0.005 #using the range function to simulate for 500 days which is the simulation days for days in range(1,simulation_days): num_infected_daily = (infection_rate * total_infected * susceptible)/total_population # get the susceptible number for next day total_susceptible = total_susceptible - num_infected_daily num_recovered_daily = recovery_rate * total_infected num_dead_daily = death_rate * infected total_infected = total_infected + (num_infected_daily - num_recovered_daily - num_dead_daily) total_recovered = total_recovered + num_recovered_daily total_dead = total_dead + num_dead_daily susceptible_list.append(total_susceptible) # adding to the list of susceptible people infected_list.append(total_infected) recovered_list.append(total_infected) dead_list.append(total_dead)
Now that we have simulated Konvid-18 for 500 days, we can now visualize our result.
Visualizing the result# Using chúng tôi to plot plt.plot(range(0,simulation_days),susceptible_list,color='blue',label='Susceptible') plt.plot(range(0,simulation_days),infected_list,color='red',label='Infected') plt.plot(range(0,simulation_days),recovered_list,color='green',label='Recovered) plt.plot(range(0,simulation_days),dead_list,color='orange',label = 'Dead') plt.legend() #add the labels to the plot plt.title('Konvid-18 Disease Simulation in JavaGo city') plt.xlabel('Days') plt.ylabel('Total Population') plt.show()
After running the above code, the image below will be displayed.
Visualization Result. Image by AuthorDeductions Conclusion
The article has shown you the importance of mathematical models, how to model diseases with the SIRD model, how to automate the process for days, and how to visualize it. The article introduced you to the SIRD model, there are other mathematical models that you can explore further and dive deeper into like the SEIR, SIS, SIRV e.t.c. The article also didn’t cover the mathematics of deriving the contact ratio, recovery rate, and death rate, you can explore these concepts further. I hope you have realized the importance of mathematics in the healthcare industry.
I created a demo web app for further exploration, the web app was developed with streamlit. You can access the web app with this link and check the source code with this link.
You can connect with me on LinkedIn,References/More Resources
(3) The MATH of Epidemics
The media shown in this article on SIRD Model are not owned by Analytics Vidhya and are used at the Author’s discretion.
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