This article provides an introduction to the world of big data to sociologists. It talks about the possibilities of using big data to identify new phenomena in human behavior. It also goes over the potential pitfalls of relying on big data and makes the case that big data works best when used in combination with other methods rather than in isolation. It concludes with what the future could hold for using big data for Sociology.

This article is an appropriate bookend for this semester. It goes over the major themes that we covered in detail in our classes and provides a good summary of the things we’ve learned. On noticing that this article was published in a Sociology journal, I was reminded that despite all the computing related things we’re doing, the ultimate goal is to further the study of humans in this connected world. All the machine learning and data analysis was a means to an end, which is obvious in retrospect but is not really in the forefront of your mind when you are deep in the throes of writing code.

The authors made an interesting point about scientists fixating on single platforms like Twitter, making the comparison to ‘model organisms’ in Biology. Behavior on Twitter is exclusive to Twitter and doesn’t necessarily reflect the wide range of human behavior. But even within so-called model organisms, there is such a rich research potential for studying human behavior. I don’t believe that findings need to be generalizable to be useful. Interesting observations can be made on single platforms and there is no need to constantly consider how generalizable the information is. Consider Finstagrams [1], a phenomenon where users are creating secondary accounts to be viewable by only select people. Regular Instagram accounts are often curated to be perfect and public facing. Finstagrams provide an outlet where users can just ‘be themselves’. I believe this could be a fascinating study, looking at what causes a user to make a Finstagram account, when did they first start appearing, what are the real world analogues, and so on. Looking at single platforms exclusively should not be dismissed for lack of generalizability for sometimes it is that lack of generalizability that makes findings interesting.

I think there is an interesting future ahead for this combination of Sociology and Computer Science. With everything that is happening with Facebook and the problems that arise from social media in general, I think this field holds the future in figuring out how to help solve the problem of humans in the online world, just like Sociology is trying to solve the problem of humans in the real world. It warrants keeping an eye out and seeing where things go from here.

[1] https://medium.com/bits-pixels/finstagram-the-instagram-revolution-737999d40014

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[1]- Robert M. Bond, Christopher J. Fariss, Jason J. Jones, Adam D. I. Kramer, Cameron Marlow, Jaime E. Settle and James H. Fowler, “A 61-million-person experiment in social influence and political mobilization”

[2]- Adam D. I. Kramer, Jamie E. Guillory, and Jeffrey T. Hancock, “Experimental evidence of massive-scale emotional contagion through social networks”

SUMMARY:
Both these papers talk about influence of social networks on individual’s decision making. The first one talks about ‘desirability’ during the US election: I Voted Button whereas a page that gave users information regarding the election (polling booths location,etc) to check user engagement. It was no surprise that they found the I Voted Button more prominent. The second paper manipulates (in a controlled environment) the number of user posts in sad and happy moods and then studies the kind of post a user, under this influence posts. They found that the users who had been exposed to positive posts tended to put in positive posts themselves.

REFLECTIONS:

Mob mentality has been a problem since the time of Caesar and the power to influence and sway it comes with much responsibility. The first question that one would ask is if the second study ([2]), while within the User Terms and Agreement on Facebook, an ethical one? Should it be ok to toy with users’ emotions in the name of science? In our everyday lives, we may be led to read various kinds of posts that may influence to behave one way or the other, and while this is again a huge bone of contention, should we allow social media giants to control what comes on our feed to give us a largely positive experience?  Also, in their experiments, the authors don’t seem to consider how positive or negative a post is. An intense positive post can often drain out a lot of negative emotion. This can also be harnessed to useful ends by charities and other NGOs that aim at helping people. Many sad stories followed up by a positive one (caused by users online) can influence other people to help and also ‘restore faith in humanity’.

The first study([1]) on the other hand has probably given rise to a lot of positive movements on Facebook. When people see their friends donating and supporting causes and movements, they feel the need to do it themselves as well, whatever the motivation may be.

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Social influence is a well-known phenomenon that individuals and groups experience through their social interactions. there are multiple aspects of social influence. Individuals may feel pressured to practice some behaviors or follow some beliefs influenced by their close social circle.  People also get affected by the emotions of others surrounding them. Some people use the expressions, happiness is in the air, or depression is in the air to express their perception of a surrounding emotion.

With the prevalence of online social platforms, many questions arise regarding how social influence is shaped, and how it affects and/or is affected by real-life social interactions. In their work A 61-million-person experiment in social influence and political mobilization, Bond et al. studied the effect of social influence on encouraging people to vote in elections. Their experiment consisted of conveying a message to individuals through their Facebook Newsfeed that encourages them to vote and let others know that they did. The message also showed some of an individual’s friends who already voted. Their results indicate a significant influence on an individual when he knows that people in his close circle have taken an action, pressuring him to take a similar action.

In another study titled Experimental evidence of massive-scale emotional contagion through social networks, the core data science team at Facebook showed how a decrease in posts with positive emotions in someone’s Newsfeed rendered him less positive, while a decrease in posts with negative emotions rendered him less negative. Their work presented an experimental evidence of the phenomenon known as emotional contagion.

The two aforementioned studies analyze two different aspects of social influence and how they are shaped in online social platforms. My reflection on these studies could be summarized in the following points:

1. A common point between the two studies is that both provide a perspective on how to interpret the effect size. An effect size that may seem small in an experiment on a tiny subset of a giant social platform such as Facebook should be taken into consideration given how the aggregate effect could be.
2. The first study claims that the influence of close friends (strong ties) is much significant than the influence of other friends (weak ties) where the number of interactions is much less. I would be interested to study the influence of social media public figures which some people like to call them social influencers. These social influencers may have a significantly large number of apparently weak ties, however, their aggregate effect is more significant than smaller number of strong ties.
3. Given some experimental evidence on some aspects of social influence, it is interesting to study how this influence could be used for opinion manipulation. During the Arab Spring uprisings, social media played a pivotal role in shaping the public opinion, which I believed contributed significantly to today’s outcome in many countries, e.g. Egypt.
4. The emotional contagion study refuted the claim that a trending positivity in the Newsfeed may lead to a negative effect on an individual. However, it is hard to conclude this from only the outcome of this study, as there might be another perspective where an individual is pressured to act positively to comply with the trend.

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[1] R. M. Bond et al., “A 61-million-person experiment in social influence and political mobilization,” Nature, vol. 489, no. 7415, pp. 295–298, 2012.

[2] J. E. Guillory et al., “Editorial Expression of Concern: Experimental evidence of massive scale emotional contagion through social networks,” Proc. Natl. Acad. Sci., vol. 111, no. 29, pp. 10779–10779, 2014.

<Jots>

<1>

Ethical issues abound.

<2>

When one observes (key word) a close friend to be in a negative mood, we internally pick one of two choices: fight or flight (broader term: arousal).

Given, if the connection is strong, the probability of choosing the former, fight, will be high.

Although, the probability is dependent on the psychological character of the actor, given that most of us belong to one that exhibits positive attitude towards helping people fall into a category that would “fight.”(assumption may be challenged)

Given, the above, our minds go into a state which is ideal from helping another combat certain issue. This state allows one to put oneself in another’s shoe: empathy.

Can being in this state reflect in oneself?

If so, isn’t it a good characteristic, one that makes us human?

<3>

But how does one separate empathy for a close few from a group.

Can this empathy turn into allegiance leading to group thinking?

Is censorship a good way to tackle this? As a proponent of democracy I don’t think so.

Such effects can be negated through more diverse opinions in the public forum. But isn’t this affected by entities that restrict the access to these channels.

<4>

Also, doesn’t it mean there is a lack of forums which are designed to be available for everyone. Designed to be fair. This is definitely a moonshot as “human forum” (society) evolving for millennia hasn’t found the global optima (solution). But, this shouldn’t be a deterrent.

<5>

If one is pushed into a negative mood valance, would you be able to understand another’s state? Study [3] shows we’re less able to resonate with other people’s pain when we’re feeling down. Wouldn’t this mean the assumption of the authors of [2], of having equal probability of sharing information by a person being subjected to the experiment is wrong?

[3] Li, X., Meng, X., Li, H., Yang, J. and Yuan, J., 2017. The impact of mood on empathy for pain: Evidence from an EEG study. Psychophysiology, 54(9), pp.1311-1322.

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1)- Robert M. Bond, Christopher J. Fariss, Jason J. Jones, Adam D. I. Kramer, Cameron Marlow, Jaime E. Settle and James H. Fowler, “A 61-million-person experiment in social influence and political mobilization”

2)- Adam D. I. Kramer, Jamie E. Guillory, and Jeffrey T. Hancock, “Experimental evidence of massive-scale emotional contagion through social networks”

Summary:

Both papers examine social influence in online social networks (which is Facebook in both). The first paper studies if political behavior is contagious and can spread through an online social network, as it measures a social message on Facebook can influence users to vote during the US congressional election vs an informational message. They also measure the influence of friendship on Facebook in encouraging users to participate in the voting process. The second paper studies the emotional contagion on Facebook users and can controlling the percentage of emotional news and activities in the news feed could affect the Facebook user. Also both papers verify that the effects of face-to-face or non-verbal communications to propagate emotions and ideas are similar to those verbal/textual communication on social networks.

Reflection:

• In the first paper the authors divided their test groups into unbalanced three groups: the social message group (n = 60,055,176), the informational message group (n = 611,044) and the control group (n = 613,096). I do not know why they dedicated most of their test subjects to the first group (they did not give an explanation for that)
• The experiment in the second paper made me think that I have to read carefully the terms of use and privacy conditions of whatever social media I sign up to. Clearly the experiment is legal but is it ethical? Should Facebook experiment people and manipulate their emotions. I wounder what else they are testing?
• Facebook news feed proved to be a powerful tool that can affect one’s emotions, mood and beliefs. I would like as a Facebook user some control over my news feed with respect to the type of emotions that the news hold. I would like to filter in/out posts and news related to my preferred mood. If this tool can classify the current post/activity into emotional/mood statuses and then later give the user the ability to control what to be displayed based on his/her target mood(s). This tool could also include an emotion-o-meter of the current news feed whether it is positive or negative or just normal news. This tool could help users maintain their well-being and mental health and measure how toxic their news feed is.

• In the second paper, the authors collected data for one week (January 11–18, 2012). I wonder if it was better if they collected data in some other period, since that time of the year is right after Christmas where people have recent positive emotions which might affect their online behavior and reaction to their news feeds.
• The second paper gave me an idea about enhancing the text-based sentiment analysis classifiers after adding emojis as features into the classification models

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1. A 61-million-person experiment in social influence and political mobilization
2. Experimental evidence of massive-scale emotional contagion through social networks

61 million Facebook users received a special social message at the top of their News Feed, on the day of the Congressional elections, which included polling-place link; “I Voted” button, with a counter showing how many other Facebook users had previously reported voting; and also pictures of the user’s friends who had reported voting. There were also two other groups of users who were randomly selected (about 600000 users): One group received Informational message that was like Social message but with no pictures; the other received no voting message at all.

The results of this study showed that users who received the informational message voted at the same rate as those who saw no message at all. Authors estimated that the social message directly and indirectly increased voter turnout by 60,000 and 280,000 votes respectively (340000 votes in total).

In second research, researchers performed an experiment (manipulating the emotions of users[1]) with Facebook users to test whether emotional contagion occurs between users by reducing the amount of emotional content in the News Feed. They showed that when positive expressions were reduced, the positive posts and more negative posts are produced by users and vice versa. These results indicate that users’ emotions can be influenced by other users on social networks (emotional contagion).

The upcoming political election, is a good example for both research because it can be a potential source for emotional contagion. In these days we can see posts, memes, and many articles in every social network about the negatives/positives of each candidate which can lead to mixed emotions. Advertisements are focusing on the negative behaviors of candidates and also topics like taxes, guns or other high conflict topics which can increase anger, distress and sadness and can be spread unknowingly between people.

The authors of the first research also published another paper[2] recently with the same research topic and approach but this time for 2012 presidential election. Facebook also did another research to see if they could influence voter behavior. Their results showed that Facebook could play a considerable role in influencing how people vote. They actually, changed the News Feeds of 1.9 million users and studied how they behaved, which lead to a 3% increase in the number of people who voted[3]. I think the results of all of these research show the considerable impact of social networks on user’s emotions. I mean these results depict how social networks benefit from the existence of social contagion.

As mentioned, the first research focused more on the effect of social messages in Congressional Elections (the effect of social contagion on voting). I think if we study the social influence in social networks, we should also consider the effect of influencers, especially in important events such as elections. Influencers play critical role in information dissemination during the election days. They are unique and drive huge amounts of engagement, and discussion. Their millions of followers can make or break a campaign with just one video. So they can influence voters’ behavior. For example, in 2017 Iranian presidential election, I remember an influencer only used the color of one of the candidates (each candidate had selected a specific color for her/his campaign) in her profile picture. Then, many people started to use that color in their profile picture and after that this behavior spread between people. Many people even didn’t know who started using this color in profile picture, but because they saw their friends, families or other people were using this color, they wanted to show they are among them too.

[1] https://www.businessinsider.com.au/facebook-study-emotional-states-transfer-2014-6#ixzz3HkSqIikX

[2] Jason J. Jones et al. “Social influence and political mobilization: Further evidence from a randomized experiment in the 2012 U.S. presidential election” April 26, 2017https://doi.org/10.1371/journal.pone.0173851

[3] https://www.businessinsider.com.au/facebooks-news-feed-voting-experiment-2012-2014-10

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Paper 1: A 61-million-person experiment in social influence and political mobilization

Summary:

The authors study the effects of social influence for effecting behavior change. The results of their randomized controlled trial of political mobilization messages shows that these messages influence users’ political self-expression and real world voting behavior. The results also indicate the importance of social ties in spreading real and online behavior in humans.

Reflection:

The users were unevenly divided into the three groups with number of people in ‘social message’ being much larger than the ones in ‘informational’ and control group. But otherwise the experimental design and the way real life behavior was observed (by checking the public voting records) is amazing!! Also the scale of their experiment is huge!

The authors don’t mention if they were aware of the political leaning of the users or whether the dataset was balanced with equal no. of democrats and republican supporters. I read online that FB received backlash for this research since the dataset is assumed to be skewed towards democrats and it was claimed that the study influenced the voting results since more democrats came to vote.

The authors “arbitrarily” define close friends as the ones lying in the 8^th percentile or higher of frequency of interaction among all friendships. I’m not clear about this assumption. Was it just done so that in their dataset 98% of people end up having atleast one close friend (the avg being 10).

One of the premise in the paper is that social ties are crucial in spreading real and online behavior in humans. If that’s the case, can it be exploited to make people come out of filter bubbles. If we are able to identify “close friends” with opposing political ideologies and rank their political posts higher in the feed, will it make people click on the shared content?

Both papers are great examples of how social media can influence human behavior and thus the importance of social computing research.

Paper 2: Experimental evidence of massive-scale emotional contagion through social networks

Summary:

In this paper, the facebook researchers study emotional contagion outside of in-person interactions between individuals by modifying the amount of emotional content in News Feed of about 0.68 million people. The results of the study showed that displaying fewer positive updates in people’s feeds causes them to post fewer positive and more negative messages of their own. People who were exposed to fewer emotional posts in their News Feed were less expressive overall on the following days.

Reflection:

Design of Experiment: Not much information is given about the 0.68 million people selected for the experiment. Gender, age group and demographics can control the results of such an experiment. So knowing these details would have thrown more light on the results.

The researchers determined whether a post is negative or positive depending upon if it contained atleast one positive or negative word. I’m not convinced about this strategy of classifying facebook posts.

People who posted at least one status update during the experimental period were selected for the study. The threshold of one seems too less to claim the emotional state of a user.

Evaluation of results: Have the author’s considered scenarios where some event could have lead people to post more positive/negative posts [e.g home country winning a sport event etc], rather than the effect of emotional contagion.

The way people express their emotions on FB is complex [use of sarcasm, double negatives, images along with text etc.] So I’m not convinced that counting total number of positive and negative words accurately depicts the emotional state of a user. It seems very naïve. [Paper “Does counting emotion words on online social networks provide a window into people’s subjective experience of emotion? A case study on Facebook.” challenges the same belief]

Ethical consideration: The paper says ‘it was consistent with Facebook’s Data Use Policy, to which all users agree prior to creating an account on Facebook, constituting informed consent for this research.’ I wonder if the participants whose feed were affected were personally informed and if they explicitly agreed to be a part of it. If a study is expected to negatively affect someone’s mood, then I believe explicit consent is required.

Overall I’m still skeptical about the main claim of the paper “results suggest that the emotions expressed by friends, via online social networks, influence our own moods”. I believe other’s emotions might affect what we express on social media, but in no way it is a representative of the user’s actual emotional state.

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Papers:

[1] Experimental evidence of massive-scale emotional contagion through social networks – Kramer et. al.

[2] A 61-million-person experiment in social influence and political mobilization – Bond et. al. 

Summary:

[1] talks about emotional contagion in social networks; how emotions expressed by others influence our own emotions. It hints that these effects may even be long term, and are often subconsciously experienced. It tries to quantify whether seeing positive posts on their feed makes a user themselves post more positively, and vice versa. 

[2] also talks about the importance of social influence for effecting behavior change, but it focuses on social contagion in actions rather than emotions. It randomly showed users either an informational message (i.e. statistics about how many people voted, and encouragement to vote), a social message (i.e. profile pictures of friends who voted along with the informational message) or no message, and analyzed the effects of the messages on users, and also analyzed the effects of close friends getting the message on users.

Reflection:

The authors in [1] state that they determined a post to be positive or negative if it contained at least one word which was positive or negative according to LIWC respectively, but this seems to be a fairly weak way of measuring the emotional content of the post, and the data might contain lots of “weakly positive” or “weakly negative” posts.

[1] was also an interesting insight into statistical analysis. It used a weighted linear regression model to test the hypothesis. The authors took care to try and reduce the effects of other factors, by ensuring that the subjects had no significant deviations in their emotional expression during the week before the experiment, and conducted t-tests to check the correlation between variables.

However, since emotional state is a complex thing to quantify, and since the sample size was so large, there is a lot of scope for external unforeseen variables which might muddy the results. Since the sample size is large, small effects can be found to have “significant” p-values. Moreover the effects of social contagion were not very pronounced. The percentage of change in number of words of a particular emotion used by a user after changing the news feeds were less than 0.1%.

As the study in [1] was only conducted over a week, studies can also be conducted to see the effects of emotional contagion for shorter or longer periods of time, or measure the rate of change of emotional word usage over time.

In [2], since a major factor in deciding whether users would vote or become interested in voting were the close friends of the user, the results become hard to isolate from effects beyond social media. This is because user’s have plenty of real world interactions with close friends, and this might be what influenced them to vote, not the messages on social media.

Interestingly, in [2], the users who saw the social message were 0.39% likelier to actually vote, but 2.08% likelier to say they voted. This hints that users are aware of the social stigma that comes with not voting, and often the validation from their peers for having voted is a stronger driving force than the inherent desire to vote. Maybe a system can be designed so that only verified voters can click the I Voted button, and the effects that has on voting patterns can be analyzed.

The probability of encouraging a user to vote through online social contagion is found to be quite small, although the authors do (rightly) state that even the small effects can have large consequences, since voting races are narrowly decided. 

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Paper 1: Bond, Robert M., et al. “A 61-million-person experiment in social influence and political mobilization.” Nature 489.7415 (2012): 295.

Paper 2: Kramer, Adam DI, Jamie E. Guillory, and Jeffrey T. Hancock. “Experimental evidence of massive-scale emotional contagion through social networks.” Proceedings of the National Academy of Sciences (2014): 201320040.

Bond and Kramers papers on social influence analyze how sentiment and movement is inspired though the social network. Bond et. al. study how much effect a peer network has on the voting action and interests in over 60 million people. Kramer et. al. study how positive and negative posting behavior stems from from seeing other users positive or negative expressions on social media. While both papers study how influence is shaped on social media, they present contrasting results.

Bond et. al. say that peer influence is more important that impersonal nudging. For example, people who saw their friends voting, were more likely to open the link to the nearest polling station. Also they were more likely to engage in self expression and offline action. Even though the data is massive, there is no measure of approximately how many people who select “I voted” sticker, actually vote. Also, they mention that clicking on the link pointing to the nearest polling station was considered as expressing additional interest. Most of the times, the polling stations are locally very well known and frequented by the voters. For example, schools, supermarkets, community places etc. Therefore, it is possible that users who did not click on it, simply did so because they already had the information they needed. To avoid and even identify such limitations, qualitative study of representative sample of users could have been done. This study could have included surveying for reasons of voting and whether their Facebook friends had anything to do with it. Further, this whole paper studies social influence through only one issue: voting. Voting in general is considered as a relatively low trouble and positive activity. It will be interesting to see what effect peer influence can have on activities that take some effort such as vaccination, donation, cleaning drives and awareness campaigns.

The second paper makes seemingly simar but still contrasting claims to the first paper. Kramer el. al. claim that emotions are transferred over social media just by being exposed to others emotions rather than the actual event. This might suggest that a few strongly opinionated users might be deciding the emotional state of their entire peer network. Social media can be said to be lead by virtual extroverts. This makes it even more important for users to get exposed to cross cutting views to avoid getting influenced by a few loud friends. What is different in this paper is their claim about this emotion transfer not being a conscious effort. Firstly, without a good qualitative analysis, strong causality between emotion transfer can’t be made. Secondly, in Bond et. al.’s work, suggests that users are motivated by their friends decision to vote this indicating their conscious decision to value their friends actions over strangers.

Both of the experiments were interesting and had massive dats. I would be interested in discussing the ethical side of their data collection effort and what is reflects about privacy on social media.

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[1] R. M. Bond et al., “A 61-million-person experiment in social influence and political mobilization,” Nature, vol. 489, no. 7415, pp. 295–298, 2012.

[2] J. E. Guillory et al., “Editorial Expression of Concern: Experimental evidence of massive scale emotional contagion through social networks,” Proc. Natl. Acad. Sci., vol. 111, no. 29, pp. 10779–10779, 2014.

The two papers talked about social contagion and its effects in two perspectives which I feel are complementary to each other. The first paper talks about political self-expression being influenced by different levels of engagement on social media.

This reminds me of:

“In individuals, insanity is rare; but in groups, parties, nations, and epochs, it is the rule.”

― Friedrich Nietzsche

This was a quote my mother used to refer to every time I went on trips with my friends warning me of her self-coined (I believe) phenomena of “temporary group insanity”. She kept narrating how monkeys near her home in her childhood used to act crazy watching other monkeys do it. I believe the social norm translating through a network with the need for an increased “tie strength” with nodes (in this case humans) that are perceived to be our networks “center” or an important node defining our network structure is what drives humans to follow their “close friends”. This is a psychological and philosophical take on the findings in the paper. The tool called ‘sense-making’ is a Human-Computer Interaction perspective on how humans tend to reason with the cues in the environment before processing it to take a decision. A meta-cognitive process involving situation awareness and cue saliency is the concoction, I believe, that controls an individuals decision to follow a friend or group of friends into political self-expression. As the paper states, this is not helping improve their social status or the research has no indication of it. There is no compelling social reason for us to click the “I Voted” button like peer-pressure. But I believe that since we are accustomed to following our formed set of heuristics it is easy for us to remain consistent, go with what is available, more familiar and appealing to one’s ‘affect’. These will generally point to taking a decision that helps us recognize ourselves as a part of our perceived group of ‘friends’ or ‘close friends’.

The question of whether we are in a time when we are at the “end of theory” resonated, even more, when all the paper did was use the millions of data points to infer a finding rather than hypothesize something or use the data to find a grounded theory about the behaviour of the individuals or groups.

From the point of quantitative analysis procedure that the paper follows the group I believe did a good job of designing the experiment with the controlled, informed and social groups with a backed inferred definition of ‘friends’ and ‘close friends’. I would like to see if the same could translate to other venues like Amazon.

• Would information about our ‘close friends’ or other people we relate to buying a product influence our decision to buy or not buy a product?
• Would it be the same with movies on Netflix?
• Can we use the information we can scrape from people who log-in on Amazon, Netflix with their Facebook IDs about their close friends to map the sort of products people would want to buy helping improve their experience?
• Will this be overdone if we used an algorithm to keep track of a social network of an individual to then curate the content he or she sees?
• Is this a new type of profiling?
• Is this ethical?

The reason I ask so many questions is the alarming realization one can come to from the conclusions that the paper draws. After the propaganda that the authors talk about towards the end, they elude to the fact that social influence can impact behavior not only online but offline as well. This reminds me of the dystopian society represented by the TV series “Black Mirror” where corporations control the way we think and behave.

Coming back to reality and putting the researcher hat back on, the second paper was more catered for the interests I have. Here the authors try to show the existence of emotional contagion. The papers attempt at establishing influence and interaction on social media platform is one of interest for me. The question of whether a persons expression is captured only by the text they input onto their walls or comments on others posts is very important. Do things like videos one clicks on, likes expressed, emojis sent, etc. influence the positive and negative emotion one expresses? If there is a shift in the norm of a community, which could be a scenario one can draw from the paper, where many community members are expressing negative emotions does this influence our “behavior” just in that community or overall?

For example, if John is your average inquisitive teenager who is adventurous and is a part of this online community on E-Sports. Initially, the community is well controlled or monitored or moderated. After a few months, the new and a few old members (let’s say a majority) start expressing a lot of aggression. Now at this point, John identifies himself with the community and does not want to feel left out so starts putting a facade of aggression for the members to accept him. He spends the time when he is not on the community watching cat videos and helping the elderly as he is a youth volunteer.

Now the question is, “Does exposure to the negative emotion on the community show emotional contagion and influence his behavior?”

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