1. Garett, R. Kelly (2009) – “Echo chambers online? Politically motivated selective exposure among Internet news users”
2. Resnick, Paul (2013) – “Bursting Your (Filter) Bubble: Strategies for Promoting Diverse Exposure”- Proceedings of CSCW ’13 Companion, Feb. 2013.

One of the essential elements of having a democracy is the presence of free press. This right to unrestricted information although with some exceptions, has given us people, the ability to make informed decision. But in recent years, the delivery of such news is through channels which aren’t fair, through the use of personalized recommendation systems. The paper discussed below tries to answer pressing questions from this domain.

In [1], the author tries to look into selective exposure in news readers and tries to see if they are motivated colored by one’s political opinion through the use of a web administered behavior-tracking study. In order to gain better insights the author gives out five hypotheses listed below.

1. The more opinion-reinforcing information an individual expects a news story to contain, the more likely he or she is to look at it.
2. The more opinion-reinforcing information a news story contains, the more time an individual will spend viewing it.
3. The more opinion-challenging information the reader expects a news story to contain, the less likely he or she is to look at it.
4. The influence of opinion-challenging information on the decision to look at a news story will be smaller than the influence of opinion-reinforcing information.
5. The more opinion-challenging information a news story contains, the more time the individual will spend viewing it.

Given the how dated the publication is, I wonder if the conclusions of the paper are still relevant. The major channel through which news is delivered has shifted to social media. Here the options are limited given that the content is prefiltered and delivered only if the chance of one clicking it is high. Also, the content you are given exposure to, depends on your “network”. Given these features of the mode of delivery, the authors conclusion, I believe, would definitely be challenged.

Also, one might even question the validity of the authors claim due to lack of diversity of the sample group and how the sample group was selected. Given how the exposure of survey on different news sources were, the group of people who were willing to participate may not have been the true representative of their groups. 

It would have been an interesting experiment if the author chose a wider variety of groups from a diverse political background and analyzed the group behaviour of the same and compared them with each other.

Another experiment that would be have been interesting if conducted would be to see how the behaviour of the user group changes when reading about a particular topic post exposure. Do they stick with the opinions of the first article or do they venture out to challenge it? Given that we are exposed to topics of interest everyday, I believe, a long term exposure study is needed to track the echo chamber effect which is missing in paper [1].

Paper [2] gives reasons for the need to develop products which promote diversity and exposes users to many opinions fostering deliberative discussion. The paper, then goes on to discuss few examples of such products.

Can the user groups be nudged towards good behaviour? I believe that is definitely possible. But, how can one achieve that in a equitable manner? Could it be that certain users are more vulnerable to nudging and others aren’t? Would the data obtained to do so by private entities like social media companies be put to use in the right manner?

I believe some oversight on the above by some third-party is necessary to ensure the same.

Read More

1. Garrett, R. K., “Echo chambers online?: Politically motivated selective exposure among Internet news users”, (2009)

2. Resnick, Paul, “Bursting Your (Filter) Bubble: Strategies for Promoting Diverse Exposure”, (2013)

Summary:

The first paper is about the selective exposure of online news, whether a user’s consumption of online news based on his political background or not. The author conducted an experiment on 727 online users from two news websites (AlterNet and WorldNetDaily) with different political leaning (left and right respectively). The author tracked their usage and browsing behavior. Each user was given a set news articles about different political controversial topics. The results of this study suggest that opinion-reinforcing storied gets more exposure while opinion-challenging articles get less exposure. He also found that users do not avoid opinion-challenging news and spend some time reading them.

The second paper mentions different strategies developed to diminish selective exposure and promote diverse exposure of information among online users.

Reflection:

– I would prefer if the author of the first paper conducted a longitudinal study and later asked those users how the exposure to opposite point-of-view would challenge their beliefs and how far it might change it.

– I would like also to design a method that presents the counter-attitudinal opinion/news in an acceptable way for the users without triggering their beliefs’ self-defense and reject the information from the opposite side. May be this could be achieved by merging different strategies mentioned in the second paper.

– Those papers inspire me to build a database of profiles of news media (broadcast and online). I would collect data such as their political leaning, their stance towards popular and controversial topics, their credibility. I would also record their connectivity to each other and to real world entities (such as countries, governments, parties, businessmen … etc). I would also give each of them different metrics representing how much they broadcast misinformation (rumors and fake news). I believe such dataset would be very beneficial.

– I would like to measure how far the selective exposure of news articles on online news website different from the news that appear in the news feed of Facebook and twitter. I mean would the personalization of news feed on Facebook and twitter be similar to our selection on online news websites.

– I want also to study if people of similar political backgrounds are clustered together on Facebook and twitter (I mean from the network analysis view). Does me and my online friends (on Facebook) share similar beliefs and political preferences and how often we appear in each others news feed (our posts and comments).

– In my opinion the reading time metric is irrelevant and misleading. Since the reading time of each article depends on different factors such as the article length (longer articles need longer time to read), the vocabulary and language difficulty (which might the user reading speed) and also the education levels of the users (which will clearly affect their reading speed and information digestion).

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Papers-

[1] Echo chambers online?: Politically motivated selective exposure among Internet news users – Kelly et. al.

[2] Bursting your (filter) bubble: strategies for promoting diverse exposure – Resnick et. al.

Summaries-

[1] discusses how user’s political leanings affect how they interact with news articles. It collects data from hundreds of users of news sites, and conducts a behavioral tracking experiment to see whether users prefer to interact with content they agree with or content they disagree with. It finds that users are less likely to interact with information they disagree with, but they do not actively avoid it. It constructs five hypotheses, considering whether users look at information which supports or detracts from their own viewpoints, and how long they spend looking at these articles.

[2] is a very short survey type paper, which, after quickly defining the need to design tools to provide diverse exposure and discourse on the Internet, goes on to discuss some implementations try to address this problem by helping users understand the biases of the content they consume, or to consider/explore alternate perspectives, or engage in discourse with a wide variety of viewpoints.

Reflection-

[1] is an interesting read, and makes some fascinating claims, but it has a few flaws. Firstly, it was published around 2009, which was right at the dawn of the age of machine learning for recommender systems. This meant that most websites did not have user specific curated content at that time. The hypothesis discussed by the article, which suggests that the internet may not create echo chambers, since users are not particularly averse to looking at views which go against their own, is not as valid in today’s world. Due to automatic recommender systems, users do not have a choice in this matter anymore, and may be continually exposed to partisan information simply because of their prior information usage patterns.

Secondly, the paper admits that the selection of candidates for the study was not exactly a good representation of the entire nation. The users who signed up for this study already had strong political views, since they were active on either a left leaning or a right leaning website from before. Moreover, more than half of them had a college degree, and the ethnicities of the participants were heavily skewed.

Interestingly, [1] mentions that while only 20,000 people saw the recruitment statement on the left-leaning website (AlterNet), 100,000 people saw the statement on the right-leaning website (WorldNetDaily). However, both sites were almost equally represented in the final selection of candidates, despite the recruitment statement being seen by 5 times as many people on WorldNetDaily. This could hint at an inherent “willingness to participate” of left-leaning people, or might simply be because the readers of the left-leaning site had a lower income on average (as claimed by the paper), and thus desired the participation prize more.

[1] also makes a claim that opinion challenging posts would also lead to an increase in the duration for which the user engages with the content, which is later backed by the data. However, users would probably be less inclined to immediately close articles which they disagreed while interacting with a new unfamiliar software interface, when they know they were taking part in a monitored survey, as they would be when browsing privately.

It is interesting to see that fears of rising political polarization catalyzed by Internet technologies were prevalent not just in 2009, but also as early as 2001, as indicated by the citations made by [1]. It is almost eerie to see these insights become relevant again, more than a decade later.

Many of the systems discussed in [2] would also have a tendency to become biased, depending on the beliefs of the majority share of the users of the systems. For example, if more liberals used Reflect or Opinion Space, then those comments would be more prevalent, and would receive more positive reviews from other liberals.

Opinion Space in [2] reminded me of the abstract interfaces mentioned in the Chat Circles paper, as it creates a space for users to navigate with, where users interact with different types of comments. It also changes the physical characteristics of the comments based on how the users interact with them.

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Papers : 

[1] Garrett, R. Kelly. “Echo chambers online?: Politically motivated selective exposure among Internet news users.” Journal of Computer-Mediated Communication 14.2 (2009): 265-285.

[2] Resnick, Paul, et al. “Bursting your (filter) bubble: strategies for promoting diverse exposure.” Proceedings of the 2013 conference on Computer supported cooperative work companion. ACM, 2013.

 

Summary : 

In the first paper, Garrett addresses the presence of echo chambers on our social media feeds. It studies exposure among online news readers motivated by political opinions. The paper describes the effect of opinion reinforcement and opinion challenging on exposure of online news as well as the read time for each article depending on the content of each article.

In the second paper, Resnick et al deal with strategies to curb the effects of the said echo chambers in social media feeds by introducing the concept of news aggregators and subtle nudges to users. It describes approaches such as ‘ConsiderIt’, ‘Reflect’, ‘OpinionSpace’ as mediums to do so.

 

Reflection :

The question which arises is the safety of the user data obtained, which contains the opinions of participants and how favourable they are to the reinforcement or challenge of a particular topic.

The topics of both the topic take me to my idea of the project proposal. News Aggregators seem really utile, harmless and subtle ways of curbing the Echo Chamber Effect on online platforms. Opinion Grouping could be performed to group articles and posts with similar interests and opinions into concise blocks (which can be expanded to the normal view on demand)  Thus, the concise view clubs multiple posts and articles of the same majority opinion held by the user, thereby leaving space for contrary minority opinions causing opinion challenge. This way average users get balanced opinions about the subject at hand and yet be able to scrutinize more on any opinion that they agree with or disagree with. A FeedViz like interface can be developed to solve the problem and compare which approach leads to a more informed user.

One would think that users would spend more time on opinion reinforcement, but opinion challenging articles also get more read time if the user clicks on the article even once. This is because opinion challenging articles make a user scrutinize more and dig deeper to find flaws.

Read More

[1] R. K. Garrett, “Echo chambers online?: Politically motivated selective exposure among Internet news users,” J. Comput. Commun., vol. 14, no. 2, pp. 265–285, 2009.

[2] P. Resnick, R. Garrett, and T. Kriplean, “Bursting your (filter) bubble: strategies for promoting diverse exposure,” Proc. …, pp. 95–100, 2013.

The first paper talks about selective exposure in great detail. The novelty that is presented in this paper is concerning the opinion challenge avoidance with the explanation “that people’s desire for opinion reinforcement is stronger than their aversion to opinion challenges”. The best way to capture the entirety of the argument is to present the different hypotheses of the paper as the authors present that to be the goal and set out to defend them.

H1: The more opinion-reinforcing information an individual expects a news story to contain, the more likely he or she is to look at it.

H2: The more opinion-reinforcing information a news story contains, the more time an individual will spend viewing it.

H3: The more opinion-challenging information the reader expects a news story to contain, the less likely he or she is to look at it.

H3a: The influence of opinion-challenging information on the decision to look at a news story will be smaller than the influence of opinion-reinforcing information.

H4: The more opinion-challenging information a news story contains, the more time the individual will spend viewing it.

This is reminiscent of a set of design principles that every practitioner is asked to follow, the Gestalt Principles. They are:

• Similarity
• Continuation
• Closure
• Proximity
• Figure and ground

The above principles can be interpreted to fit the current context. Humans generally try to find similarity in information to perceive information. They also always form a mental model about most subjects and task which they try and associate to the real world. In the current context, this can be related to the first hypothesis which is reaffirmed by the cognitive dissonance theory as well. Humans have the tendency to see continuity in information, even when it might not inherently exist. This is along the same lines of thought of hypothesis 3a where the influence of opinion-reinforcing information is assumed to have more influence than opinion-challenging ones. The fact that humans always try to find closure, which I would link to trying to read between the lines, is reflected in the fourth hypothesis as people generally want to know the whole story just so that they can twist it to their own narrative when necessary. The second hypothesis can be directly linked to proximity and figure and ground, in a way could be said to map to the third hypothesis as we always see what we want to as the figure and dissociate the rest to be the ground.

In general, when I try and dissect the paper there are few queries that I am left with.

• Why were the subjects not allowed to go back once their answers were submitted on a page? Would it not reveal that a participant is disinterested in going with the fact that the paper states is a dichotomous variable?
• What was the rationale with the 15 minutes? Since the entire study was carefully planned out, was there a test done to determine the time allotment for the participants?
• With the demographics of the audience as a definite skewing factor on the user data, why was no matching conducted to normalize the data to make it more representative?

A few supporting theories that I was reminded of was Group Thinking. This was presented in a book by Irving Janis in 1982 where the idea of an individual being overridden by that of the group is explained. It is relevant here as this explains how some people might be so involved in thinking in a particular way that even if they genuinely believe in an article that is opinion-challenging they just might not go with it. Another one is the paper by Z. Kunda on Motivated Reasoning. Here the author talks about how people just search for things that confirm and reaffirm what they already believe rather than searching for the actual truth.

This is a good transition to the second conference panel paper which we read on diverse exposure. This is essentially a proponent of ways to ensure that we do not have selective exposure. Though most of the panel papers background is already discussed above, the suggestion of using engagement tools like ConsiderIt, Reflect and OpinionSpace are very interesting. At the end of this reading, I have a couple of questions which I am hoping to get people’s opinion on.

1. Should social and news media nudge users to have diverse exposure? If yes, how much?
2. Does educating people about selective exposure solve this problem?

DISCLAIMER: I ask these under the assumption that diverse exposure is good.

Read More

R.Kelly Garrett. “Echo chambers online?: Politically motivated selective exposure among Internet news users.”

Paul Resnick et al. “Bursting your (filter) bubble: strategies for promoting diverse exposure.”

The assigned readings for this week speaks about the filter bubble that we’ve previously spoken about in this class. Garrett’s paper talks about the likelihood of an individual to pick a news article and the amount of time that he would spend on it depending on their ideological point. He hypothesised and concluded that individuals were more like to look at opinion-reinforcing news and would spend more time reading it if it agreed with their view point strongly. He also concluded that the more opinion-challenging information the reader anticipates in a story, the less likely he was to read it. However, he also realized that the opinion-challenging information had less effect than opinion-reinforcing information.  Resnick’s work talks about the various ways to get around the filter bubble – to be aware of them and to overcome its effects.

Many of Resnick’s proposed methods involved keeping the individual informed of the kind of news that they were reading whether it leaned left or right. In other cases, where motivated information processing was at work, his methods encourage us to identify and understand the arguments posed by the another individual with opposing views. This still does not give us a way to successfully pass on all the information that is available to us. I wonder if the most effective way to deliver such news is to present it through mediums that don’t know partisanship yet. Social and political commentary is often offered by popular sitcoms.

A dent in our hopes of eliminating partisanship through more exposure is dealt by a recent study at Duke University Polarization Lab[1]. They designed an experiment to disrupt people’s echo chambers on Twitter by having Republicans and Democrats follow accounts (automated) that retweeted messages from the opposition. After a month, he discovered that the Republicans exposed to the Democratic account became much more liberal and the democrats who had been exposed to the Republican tweets became slightly more liberal.

 

[1] https://www.washingtonpost.com/science/2018/09/07/bursting-peoples-political-bubbles-could-make-them-even-more-partisan/

Read More

[1] Garett, R. Kelly (2009) – “Echo chambers online? Politically motivated selective exposure among Internet news users”

[2] Resnick, Paul (2013) – “Bursting Your (Filter) Bubble: Strategies for Promoting Diverse Exposure”- Proceedings of CSCW ’13 Companion, Feb. 2013.

Summary

The topic for todays’ discussion is Polarization and selective exposure which means people are exposed to a certain kind of news and they are unaware of what is going on beyond that the “exposure bubble”. Selective exposures offered by a filter bubble is a result of personalized search avoiding diversified and conflicting information. These papers conduct surveys among the population using their political beliefs. The previous researches reveal that the internet news users mostly read and watch the news which conforms with their political belief (opinion reinforcement) rather than opinions which challenge their political beliefs. However, peoples use of internet to acquire political knowledge has raised concerns regarding selective exposure problem. The authors conducted a survey – a web administered behavior tracking study to access how the ones political attitude influences their use of the online news. The study used 5 hypotheses (H1 to H4) based on existing research on exposure processes. The study found that people are more inclined to look and spend more time to read new stories containing more opinion reinforcing information and that they are less likely to look and to be influenced by the opinion challenging information. The last hypothesis concluded that a person will spend more time to observe a story contradicting or challenging their opinion.  The reason being the greater the length of exposure in the news the greater opportunity for the person to refuse to view this news in the future.

 

Reflection

We were first exposed to the filter bubble effect in the paper by Hannak et al. [3]. This is a user getting exposed to information which is personalized due to their search history and might be as a result of algorithmic bias. Echo chambers scenario is mainly because of the fact of web personalization. A user is exposed to beliefs and news which are relevant to their search history and de facto their personal beliefs. It was interesting to learn that when it comes to political domain, people also spend time researching politically challenging data in order to critique the opposite idea further. Thus, being exposed to varied idea gives rise to breaking of the filter bubble, however they are not likely to alter their belief. The need for algorithmic audit is becoming clear to me.

Another important problem that may arise from selective exposure that may have a much larger negative impact is the health sector. Be it beliefs related to vaccination or other health procedures, if people who are against it are exposed only to data to support their hypothesis that may have a severe consequence. Similar to the example provided in the text, even if these group are exposed to theories contrary to their beliefs, they might use the exposure as a form of opinion reinforcement. How can we make sure that along with breaking the filter bubble, the person also becomes open to new thoughts as well?

[3] Hannak, Aniko et al. (2013) – “Measuring Personalisation of Web Search” – Procedings of International World Wide Web Conference Committee. (527-537).

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Readings:

[1] Echo chambers online?: Politically motivated selective exposure among Internet news users

Summary:

This paper studies the widely known echo chamber phenomenon. In order to carry out his experiment the author of the paper recruited subjects from readership of two different online news sites — which supported either sides of the aisle. The big question that the author was trying to address was: are people more likely to read news that supports their opinion/belief, or do people actively try to avoid news that challenges their opinion? In order to answer the big question, he made five different hypothesis, and proved them right using results from his experiment. The five hypothesis were:

1.  The more opinion-reinforcing information an individual expects a news story to contain, the more likely he or she is to look at it.
2.  The more opinion-reinforcing information a news story contains, the more time an individual will spend viewing it.
3.  The more opinion-challenging information the reader expects a news story to contain, the less likely he or she is to look at it.
4.  The influence of opinion-challenging information on the decision to look at a news story will be smaller than the influence of opinion-reinforcing information.
5.  The more opinion-challenging information a news story contains, the more time the individual will spend viewing it.

Subjects recruited for the study were not indicative of the larger US demography, howbeit the recruits from the two news sites shared various demographic similarities — hence making it possible for the author to make the generalizations and prove his hypothesis correct.

Reflection/Questions:

Whilst reading the paper I stumbled across a certain statistical number and it stood out to me — more than 85% participants were white. The immediate question I had in mind was what could be the reason for a majority white representation? More access to technology? Widespread access to education, resulting in higher interest levels in news ? The previous question was followed by how would the study be affected if the race of the participants was more diverse and more equally distributed ? This particular paper and all the other papers that I have read in this class discuss the phenomenon of filter bubbles and echo chambers, which talk about what kind of news do people consume and do they get enough exposure to opposing ideas — but this assumes a single topic(same topic on both sides); reading this paper made me interested in understanding how to deliver different news topics that people might not get exposure to because of all the different filters in online platforms. For instance someone might be reading both sides of news for gun control, but that same person might be so immersed in gun control, that he might not pay attention to poverty.

There are three more interesting ideas that I got from this paper :

1.  Exposure to how many opinion-challenging news articles would it take, either consecutively or in a very short interval, before the reader disregards the source entirely; consequentially not revisiting that source ?  (title of the article)
2. When reading an opinion-challenging article, what kind of credibility does the reader ascribe to the source ? and how does the perceived credibility of the source affect the comprehension of the news article that the reader is reading ? (source of the article)
3.  How do people react to different treatments of their views in an opinion-challenging article, and how does this impact their future take on opposing news ? (content of the article)

I think all three of these questions are very important for designing a platform where the user is exposed to opinion-challenging news in a positive manner, without being driven away or becoming resentful towards opinion-challenging news. In fact, answers to these questions might help researchers and designers in creating a platform that promotes readers to read opinion-challenging news.

[2 ] Bursting Your (Filter) Bubble: Strategies for Promoting Diverse Exposure

Summary:

This paper talks about possibly nudging people towards a more diverse exposure to news articles. The authors discourse two different possibilities of nudging people:

1. Diversity-aware news aggregators
2. Provide subtle nudges to promote readers to choose more diverse news

After detailing different methods of nudging people, the authors move onto talk about various methods that promote processing information in a motivated manner. On this end, the authors further discuss three different platforms — Reflect, OpinionSpace, ConsiderIt — that have promoted more deliberate behavior by audience indulging in divergent opinion; in other words promoting empathy.

Reflection/Questions:

During the paper, the authors suggest that “news aggregator might set a higher quality threshold..”, but this only makes think that quality is an intrinsic property and is subjective, consequentially can’t be used as a measurable attribute. One thing that all three platforms(reflect, opinionspace , and considerit) have in common is that a user has to go through more rigorous interaction with the platform, for the platforms intended operation to be meaningful — for instance ConsiderIt has its users create a pros-cons list. Not everyone has this kind of patience and/or time, so one question that I ask myself is: how can we design a platform that is not as time intensive, but still engages readers (of opposing ideologies) in a more deliberate fashion?

Read More

 

[1] Garrett, R. Kelly. “Echo chambers online?: Politically motivated selective exposure among Internet news users.” Journal of Computer-Mediated Communication 14.2 (2009): 265-285.

[2] Resnick, Paul, et al. “Bursting your (filter) bubble: strategies for promoting diverse exposure.” Proceedings of the 2013 conference on Computer supported cooperative work companion. ACM, 2013.

 

This week’s papers study and discuss the Filter Bubble effect – the idea that people are only exposing themselves to viewpoints they agree with, to the detriment of obtaining diverse viewpoints. This effect is especially prominent when it comes to reading political news. The first paper studies the reading habits of users of partisan news sites. From their results, they could conclude that the desire to seek out news that reinforces one’s own opinions does not necessarily mean that one goes out of their way to avoid challenges to their opinions. In fact, they found that people engage more with the opposing views, perhaps to try and find flaws in the arguments and reinforce their own views. The second paper is a discussion by multiple authors on strategies for decreasing the filter bubble effect such as gamifying the news reading, encouraging the users to make lists of pros and cons on issues they read, having the news sources push through opposing views if the content is high quality, etc.

The first paper’s findings that people don’t actively avoid stories that challenge their opinions very interesting to me. It means that in most cases people are willing to engage opposing opinions even if they don’t necessarily agree with them. Big internet companies that rely on providing personalization could safely tweak their recommendation algorithms at least a bit to allow some opposing views to filter through without the fear of losing business, which may have been a concern for them.

Something I would like to know, that the first paper didn’t cover is how much are the people comprehending the stories and how much does it influence them? For opinion reinforcing stories, are they tuning out once they realize that the story agrees with their opinions? For opinion opposing stories, are they spending that excess time trying to understand and does that extra engagement lead to at least a shift in their opinion from compared to their earlier stance? Perhaps this study could be done with a final quiz that asks questions about the story content and also interviews to measure if there has been a shift in their opinion.

The idea of gamifying the task of getting a person to reduce their selective exposure, through the use of a stick figure balancing on a tightrope discussed in the second paper, is a very promising idea. Stack Overflow thrives with an enormous amount of content because they have gamified answering questions. You can earn different levels of badges and that gives you prestige. Perhaps the same thing can be done to encourage people to read more widely by giving them points and badges and have a leaderboard tracking the scores across the country. People actively chase the high of getting better scores which is why I think that this might be fairly effective. Of course, you don’t want people to game the game so maybe this gamification could be combined with the other ideas in the paper of having people discuss and interact and rate the comments to prevent botting the game.

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