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Artificial Intelligence, your brain, and other things you cannot trust about politics

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A few days ago the Center for Research on Computation and Society organized a workshop with the provocative title “Six Reasons Fake News is the End of the World as we Know It“. I call it provocative because, whether “fake news” is a new thing or not, has been discussed a lot lately. Not all of us agree on what it is, or how novel it is. Some point out that it is as old as newspapers, others see it as something that mainly appeared last year. Yet others doubt that it is even a phenomenon worth discussing and that, instead of fake news, we should talk instead about specific categories such as false news, misinformation, disinformation, and propaganda.

Accepting the challenge, I gave a talk with an equally provocative, I would like to believe, title:  “Artificial Intelligence, your brain, and other things you cannot trust about politics“. You can follow my talk in the video below, but let me give you a list of the “things” that I discussed in the talk:

what-you-cannot-trusst-about-politics

I hope you find it interesting and do your own thinking about what we can trust when it comes to politics. Importantly, we need to figure out how to solve the problems of online misinformation and propaganda that seem to be all around us these days.

Or, to learn how to live with them, which is what I think will happen.

The Real “Fake News”

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The following is a blog post that Eni Mustafaraj has recently published in The Spoke. We reproduce it here with permission.

fake_news_post

Fake news has always been with us, starting with The Great Moon Hoax in 1835. What is different now is the existence of a mass medium, the Web, that allows anyone to financially benefit from it.

Etymologists typically track the change of a word’s meaning over decades, sometimes even over centuries. Currently, however, they find themselves observing a new president and his administration redefine words and phrases on a daily basis. Case in point: “fake news.” One would have to look hard to find an American who hasn’t heard this phrase in recent months. The president loves to apply it as a label to news organizations that he doesn’t agree with.

But right before its most recent incarnation, the phrase “fake news” had a different meaning. It referred to factually incorrect stories appearing on websites with names such as DenverGuardian.com or TrumpVision365.com that mushroomed in the weeks leading up to the 2016 U.S. Presidential Election. One such story—”FBI agent suspected in Hillary email leaks found dead in apparent murder-suicide”—was shared more than a half million times on Facebook, despite being entirely false. The website that published it, DenverGuardian.com, was operated by a man named Jestin Coler, who, when tracked down by persistent NPR reporters after the election, admitted to being a liberal who “enjoyed making a mess of the people that share the content”. He didn’t have any regrets.

Why did fake news flourish before the election? There are too many hypotheses to settle on a single explanation. Economists would explain it in terms of supply and demand. Initially, there were only a few such websites, but their creators noticed that sharing fake news stories on Facebook generated considerable pageviews (the number of visits on the page) for them. Their obvious conclusion: there was a demand for sensational political news from a sizeable portion of the web-browsing public. Because pageviews can be monetized by running Google ads alongside the fake stories, the response was swift: an industry of fake news websites grew quickly to supply fake content and feed the public’s demand. The creators of this content were scattered all over the world. As BuzzFeed reported, a cluster of more than 100 fake news websites was run by individuals in the remote town of Ceres, in the Former Yugoslav Republic of Macedonia.

How did the people in Macedonia manage to spread their fake stories on Facebook and earn thousands of dollars in the process? In addition to creating a cluster of fake news websites, they also created fake Facebook accounts that looked like real people and then had these accounts subscribe to real Facebook groups, such as “Hispanics for Trump” or “San Diego Berniecrats”, where conversations about the election were taking place. Every time the fake news websites published a new story, the fictitious accounts would share them in the Facebook groups they had joined. The real people in the groups would then start spreading the fake news article among their Facebook followers, successfully completing the misinformation cycle. These misinformation-spreading techniques were already known to researchers, but not to the public at large. My colleague Takis Metaxas and I discovered and documented one such technique used on Twitter all the way back in the 2010 Massachusetts Senate election between Martha Coakley and Scott Brown.

There is an important takeaway here for all of us: fake news doesn’t become dangerous because it’s created or because it is published; it becomes dangerous when members of the public decide that the news is worth spreading. The most ingenious part of spreading fake news is the step of “infiltrating” groups of people who are most susceptible to the story and will fall for it.  As explained in this news article, the Macedonians tried different political Facebook groups, before finally settling on pro-Trump supporters.

Once “fake news” entered Facebook’s ecosystem, it was easy for people who agreed with the story and were compelled by the clickbait nature of the headlines to spread it organically. Often these stories made it to the Facebook’s Trending News list. The top 20 fake news stories about the election received approximately 8.7 million views on Facebook, 1.4 million more views than the top 20 real news stories from 19 of the major news websites (CNN, New York Times, etc.), as an analysis by BuzzFeed News demonstrated. Facebook initially resisted the accusation that its platform had enabled fake news to flourish. However, after weeks of intense pressure from media and its user base, it introduced a series of changes to its interface to mitigate the impact of fake news. These include involving third-party fact-checkers to assign a “Disputed” label to posts with untrue claims, suppressing posts with such a label (making them less visible and less spreadable) and allowing users to flag stories as fake news.

It’s too early to assess the effect these changes will have on the sharing behavior of Facebook users. In the meantime, the fake news industry is targeting a new audience: the liberal voters. In March, the fake quote “It’s better for our budget if a cancer patient dies more quickly,” attributed to Tom Price, the Secretary of Health and Human Services, appeared on a website titled US Political News, operated by an individual in Kosovo. The story was shared over 80,000 times on Facebook.

Fake news has always been with us, starting with The Great Moon Hoax in 1835. What is different now is the existence of a mass medium, the Web, that allows anyone to monetize content through advertising. Since the cost of producing fake news is negligible, and the monetary rewards substantial, fake news is likely to persist. The journey that fake news takes only begins with its publication. We, the reading public who share these stories, triggered by headlines engineered to make us feel outraged or elated, are the ones who take the news on its journey. Let us all learn to resist such sharing impulses.

Looking beyond “Big Data” analysis to discover those who make a difference

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In an earlier post (Trusting Anonymous Twitter Users) I wrote about how ordinary citizens in Mexico are using Twitter to stay informed about areas of immediate risk in their cities. In our social media research we saw some anonymous Twitter accounts begin to amass large numbers of followers as they gained repute as trusted sources in the dissemination of information related to shootings, explosions and areas of danger in some Mexican cities. If you are not familiar with this earlier blog post you may want to take a look at it since I am about to describe the rest of the story as we discovered and recently published it (The Rise and the Fall of a Citizen Reporter) at the WebScience 2013 conference.

The limits of “Big Data”

While the data and the narrative we presented in the paper “Hiding in Plain Sight: A Tale of Trust and Mistrust Inside a Community of Citizen Reporters” were very interesting, my co-authors and I had the feeling that we had not discovered the full story. For one thing, who really was @GodFather, the person behind the pseudonym we had created for the prominent account in our data? Was it a real person? What if it was merely one of the successful tweet-bots that researchers have launched in the past? Or, maybe it was some guy tweeting from Scotland posing as a young woman living in Mexico. Importantly, what about the accusation that she was not really interested in the well-being of her community, but was instead working for the Zetas, the criminal drug cartel that has been accused of some of the more heinous crimes of the Mexican drug-war. Was there any truth to it?

Furthermore, there were several events that we had discovered and had not written in the paper or the blog post. Looking at the aggregate data, my co-author Eni Mustafaraj and I discovered some important developments in the lives of these citizen reporters: Shortly before the accusation against @GodFather appeared, the City had seen a lot of violence and the authorities had failed to act quickly. @GodFather had tried to organize an informant movement of  “eagles” (aguilas) on Twitter to report on the actions of the “hawks” (halcones). Hawks is the name given to low-level cartel associates working on street corners using cellphones to communicate with their bosses. These hawks are seen as important actors informing cartels about the movement of the Mexican Army and Navy so they can escape after an attack. Therefore, another distinct possibility was that @GodFather was accused because she was becoming annoying to a specific cartel.

Events in the timeline of @GodFather’s activity in our data indicated a reduction of her activity in early April, 2011. The activity of those mentioning and retweeting her also shows a similar pattern.

 

What was really happening? Was @GodFather one of the prominent citizen reporters informing the people about areas they should avoid on any given day? Was she a traitor working for the Zetas? Or perhaps a fake account? Why was she attacked, and why did she subsequently stop tweeting? Was she still tweeting from another account name or had she disappeared from the community?

 

Separating Retweets from Mentions

Another interesting data visualization separating retweets of @GodFather’s messages (in blue) from mentions of her name (in red). While in the first half of the graph her tweets (in green) seem to be echoed by the community, in the second half things change. At that time people are mainly talking about her, not echoing what she tweets.

 

Using a Berkman talk to make the connection

Though we wanted to find out more, our big data analysis was not helping much. We needed verification on the ground. But we could not contact @GodFather directly (we figured that, “Hi, I am a researcher from the US and would like to verify your identity…” would not take us far). We knew that her account had been compromised in the past, so she had every reason to hide her identity. Moreover, there existed several accounts with similar-sounding names, some of them clearly belonging to trolls attacking her, and we did not want to end up talking to them by accident!

How could we uncover the truth? The Berkman Center and a measure of good luck helped us make a breakthrough. In July, 2012, the Berkman Center asked my co-author Andrés Monroy-Hernández and me to give a talk (“Narcotweets: Reporting on the Mexican Drug War using Social Media”) on our earlier work. I knew that Berkman talks are advertised, attended and tweeted widely online. Though not very likely, it was possible that some “tuiteros” from Mexico would follow our talk live. If I told them what we had discovered, even using pseudonyms, members of the citizen reporter community would certainly recognize the real identities to which the pseudonyms referred, and perhaps they would be willing to talk to us.

Indeed, by the end of the talk (available for viewing), Mariel Garcia, a Berkman intern from Mexico who was tweeting about the talk, showed me a couple of tuiteros accounts that had shown active interest in the talk. They were offering to answer any questions I might have. Of course I jumped on the opportunity; a few hours and many direct messages later I had established connection with one of the prominent citizen reporters of the community.

From that citizen reporter Eni and I learned that we had missed an important point in the data analysis. One of the reasons that @GodFather had stopped tweeting was that her anonymity had been compromised in late July, 2011. One of the trolls that had been attacking her throughout the year revealed her real name, her street address, and her picture. Now that we knew where to look, we went back to the data and found the relevant tweets. Her pictures had been deleted on the Web but we were able to look through archives and locate several of them. Now that we knew a lot about Melissa Lotzer, the pseudonym used the by the owner of the @GodFather account, all we needed was a way to contact her. We wanted to interview her about her motives and threats she had received.

For reasons that will soon become apparent, we can reveal some details about the community we were studying. Our community of Twitter users is located in Monterrey, Mexico, and they have been using the tag #MTYfollow to stay informed about dangerous situations in their city. The prominent citizen reporter, @trackMTY (aka @GodFather) was owned by a young woman who, like many such reporters, spent many hours a day informing and being informed by her sources. Melissa Lotzer (not her real name, but the one with which she is known in the community) became an active citizen reporter in March 2010, shortly after the #MTYfollow tag was adopted by the community. The drug war had hit the town of Comales, in the neighboring Tamaulipas region, where a drug cartel was reportedly holding some citizens hostage. Melissa and some of her some friends formed a Facebook group, Mexico Nueva Revolucion, and sent an open letter to President Cardenas begging for him to send the Army to free Comales. Following the discussion on various blogs, we see that Melissa and the MNR group received credit for their initiative.

But not everyone in the community was happy with these developments; Melissa’s accounts were attacked several times by trolls. But by early 2011, her reputation in the community was strong enough that Twitter shut down some of the trolling accounts after the outcry of the community. Her later initiative to organize the aguilas movement, however, was not as successful. While more than 80 aguilasMTY accounts were created within 2 days (!) ready to support her cause, many of her old friends did not follow her in this movement. Renewed troll attacks and troll collaboration with an editor of the famous Blog del Narco proved to be too strong for Melissa’s reputation to withstand.

 

Some of the aguilasMTY accounts that were created within a couple of days in late March 2011 at the call of trackMTY

We connected with Melissa and established a trusted two-way connection. We were able to verify her identity not only from the pointers of other citizen reporters, but also because we could go back and verify her claims through our tweet corpus. You can read more about our interviews with her in the later sections of the paper The Rise and the Fall of a Citizen Reporter, and you can find our slides from the WebScience 2013 talk online.

Communities of Citizen Reporters.

In recognizing Melissa we recognize the thousand of other citizen reporters who spend long hours daily informing their fellow citizens about important and dangerous events unfolding in their cities and neighborhoods. Like most of the citizen reporters involved in supporting the communities of Monterrey, Saltilo, Reynosa, Veracruz and elsewhere, she is an idealist who wants to help others. Her experience has made her stronger despite the risk to which she has been exposed. Even after all her experience she would choose to do it all over again because, as she says:

I’m completely sure that trackmty was the reason why many people started using twitter. I receive comments daily by followers that are opening a twitter account to a family member just to follow me […] They tell me: please take care of my mom, she will be reading your tweets, she will not be reporting cases because she doesn’t know how to use a blackberry. Many similar cases like that happen every day.

Voice of Melissa Lotzer (@trackMTY) Click the play button to hear.

 

PS. We also found out more about the identity of one of Melissa’s trolls: A young clerk at a local policy station inspired by WWF characters and with a hobby of posting photographs of prostitutes and gays on his blog.

 

 

 

Trusting Anonymous Twitter Users

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Can we trust anonymous Twitter users? Before writing this paper with my colleagues Eni Mustafaraj, Samantha Finn and Andrés Monroy-Hernández, I would think that it was not impossible. But this is the theme of the paper that Andrés is presenting this week at ICWSM 2012:

Hiding in Plain Sight: A Tale of Trust and Mistrust inside a Community of Citizen Reporters

Below is a brief description of our findings. (It may look a bit impersonal because it is extracted from the contents of a poster we created, but you will get the idea.)

The contributions of this paper can be described as follows:

  1. To the best of our knowledge, this paper presents the first analysis of the practices of a community of Twitter citizen reporters in a life-threatening environment over an extended period of time (10 months).
  2. We discover that in this community, anonymity and trustworthiness are coexisting. Because these citizens live in a city troubled by the narco-wars that have plagued Mexico since 2006, it is a great example of a community where anonymity of active participants is crucial, while lack of anonymity may be fatal.
  3. We describe a series of network and content based features that allow us to understand the nature of this community, as well as discover conflicts or changes in behavior.

INTRODUCTION

The large volume of user-generated content on the Social Web puts a high burden on the participants to evaluate the accuracy and quality of content.
We usually rely on known reputed news sources (NPR, NYT, BBC, Der Spiegel, etc.) to evaluate them. However, not every country has a free press or is willing or able to allow the international press to move freely. In some countries, like Mexico, journalists have been killed by organized crime or put under pressure by the authorities to stop reporting on certain events.

In the era of social Web, more citizens are reporting of newsworthy issues gaining reputation as citizens-reporters.
However, not everywhere in the world is there a right to and protection of free speech. In countries where the traditional media cannot report the truth, anonymity becomes a necessity for citizens who want to exercise their right of free-speech in the service of their community.

Is it possible for anonymous individuals to become influential and gain the trust of a community? Here, we discuss the case of a community of citizen reporters that use Twitter to communicate, located in a Mexican city plagued by the drug cartels fighting for control of territory.

Our analysis shows that the most influential individuals inside the community were anonymous accounts. Neither the Mexican authorities, nor the drug cartels were happy about the real-time citizen reporting of crime or anti-crime operations in an open social network such as Twitter, and we discovered external pressures to this community and its influential players to change their reporting behavior.

CREDIBILITY OF CITIZEN REPORTERS

When we read news, we usually choose our information sources based on the reputation of the media organization. We trust the news organizations, therefore, we expect that their reporting is credible, though in the past there have been breaches of such trust, and all media organizations have an embedded bias that affects what they choose to report.

Social media platforms specializing in organizing humanitarian response to disasters, such as Ushahidi, rely on people on the ground to report on situations that need immediate attention. Anyone can be a reporter.

However, this poses a new problem: how do we assess the credibility of citizen reporting?
Citizen reporting lacks the inherent structures that help us evaluate credibility as we do with traditional media reporting. But sometimes, citizen reporting might be the only source of information we might have.
How can we use technology to help us verify the credibility of such reports?

HASHTAG-DEFINED ONLINE COMMUNITY

To address this question we look at a particular community of citizen reporters gathered around Twitter accounts in a Mexican city plagued by drug-related violence.

Twitter has a unique feature that facilitates on-the-fly creation of communities: the hyperlinked hashtags. While previous research has shown that the majority of Twitter hashtags have a very short half-life span (Romero, Meeder, and Kleinberg 2011), in this paper we analyze the practices of a community of citizens that have been using the same hashtag since March 2010 to report events of danger happening in their city.

We refer to the community with the obfuscated hashtag #ABC_city, which is a substitute for the hashtag present in the tweets of our corpus. We will also substitute the exact text of important tweets with a translation from Spanish to English, so that searching online or with the Twitter API will not lead to unique results.

THE BIRTH OF A COMMUNITY: #ABC_city

Through research we discovered the birth of the community defined by the hashtag #ABC_city : The following tweet mentioning #ABC_city for the first time was the inaugural one, on March 19, 2010, by a not-particularly-active member:

#YXZ_city #ABC I propose #ABC_city to inform about news and important events in our city.

Then, this user reused the new hashtag many times in the following days together with #old_ABC hashtag and others, in order to spread its use:

@userA shootings are being reported in [address] (good source) #ABC #old_ABC #ABC_city #XYZ_city

In May 11, 2010, the same user who created the hashtag tweeted the following:

@Spammer101 Stop spamming #ABC_city. It’s only about important events that might affect our society.

Between May and November 2010 the usage of the hashtag is sparse, with the old hashtags being used more often. An increase in the adoption of #ABC_city starts on November 4th, only a week before the starting period of the #ABC_city dataset.

DATA COLLECTION

We used a basic dataset and a supplemental collection informed by our initial set of data.

The original dataset consists of 258,734 tweets written by 29,671 unique Twitter users, covering 286 days in the time interval November 2010 – August 2011.
On November 2010 we provided a set of keywords related to Mexico events to the archival service. The collection was later divided in separate datasets according to the presence of certain hashtags.

To supplement our limited original dataset, we performed a series of additional data collection in September, 2011. In particular, we collected all social relations for the users in the current dataset, as well as their account information.
We collected all tweets for accounts created since 2009 with less than 3200 tweets, in order to discover the history of the (anonymized) hashtag #ABC_city that defines the community we are studying.
We also made use of the dataset described in (O’Connor et al. 2010) to locate tweets archived in 2009.

THE NEED FOR DATA OBFUSCATION

While we would prefer to give further details on the collected data and use them freely in this paper, on ethical grounds, we will protect this community under anonymity, due to potential risk that our research can pose now or in the future. To exemplify the seriousness of the situation, we provide one example out of the many documented in the press of what the lack of anonymity can lead to.
On September 27, 2011, the Mexican authorities found the decapitated body of a woman in the town of Nuevo Laredo (near the Texas border) with a message apparently left by her executioners, which starts this way:


“OK, Nuevo Laredo en Vivo and social networking sites, I’m The Laredo Girl, and I’m here because of my reports, and yours, …”

Laredo Girl was the pseudonym used by the woman to participate in a local social network that enabled citizens to report criminal activities.

THE ACCOUNT @GodFather                          

Followee Relations Out of 29,671 unique users in the corpus, we were able to collect followee information for 24,973 accounts that were active and public in September 2011 (84% of all users in the corpus). There are more than 8,5 million followee links, with an average of 336 followees per user and a median of 162 followees. The total number of unique followees is almost 1,7 million.

Ranking the followees based on the number of relations inside this #ABC_city community serves as an indicator of the attention that this community as a whole pays to other Twitter users. We inspected the top 100 accounts to understand the nature of their popularity. The top account was Mexico’s president, Felipe Calderon, followed by the TV news program of the city, and an anonymous citizen reporter to whom we will refer as @GodFather. Four journalists, the city’s newspaper, a famous Mexican poet, and a comic’s character made up the rest of top ten. Almost half of the accounts in the top 100 are entertainers of Mexican fame, with only a few international superstars such as Shakira or Lady Gaga in the mix. This statistic confirms the widespread perception that a large part of the Twitter appeal derives from its use by celebrities, though it also indicates that each community is interested in its own celebrities. 25 of top 100 most followed accounts belong to local and national journalists and media organizations, compared to 10 for politicians at the state and federal level. In fact, the governor of the state in which ABC city is located (Mexico is a federation of 31 states) ranks at the 45th position in the followees list, one place behind the account of Barack Obama.

To understand the appeal to the community of the top 100 ranked accounts, we inspected their Twitter profiles. The top account, @GodFather, has 9,079 followers inside the community, or 36% of all active members. This amounts to 16% of all his audience, he has in total 57,127 followers. @GodFather is an anonymous citizen who has written the largest number of tweets in the corpus (6,675), which make up 25% of all his statuses (26,340).

FRIEND RELATIONS
A mutual-follow relation in Twitter (the friendship) is significant because it enables the involved accounts to send direct messages to one another. Direct messages offer some privacy to users, though if an account is hacked messages are compromised (unless a user has the habit of deleting them). Communication through direct messages is not visible to researchers or the public and cannot be quantified. However, it is possible to quantify the extent to which such strong ties exist inside the community by discovering mutual links in the sets of followers and followees. As shown below, on average, 40% of user relations are reciprocated.


The normal-like histogram of reciprocal link distribution of friendship relations (mutual links) in the network of the #ABC_city corpus.

The next figure shows the graph of all members with more than 75 friendship links which only reinforces the conclusion that this is a tightly connected community of users. (We limited the number of nodes for computational reasons)


The graph of all members with more than 75 friendship links. Coloring is produced automatically by the Gephi modularity algorithm that finds communities in a network using the Louvain algorithm.

RETWEETING AS AN ACT OF CONVEYING TRUST

Past research has shown that retweeting is indicative of agreement between the original sender and the retweeter (e.g., (Metaxas and Mustafaraj 2010; Conover et al. 2011)). Over time, retweets are effectively providing information about a community of social media users that are in agreement on specific issues. Otherwise, the chance of a community member retweeting a message of an opposing political community is under 5%.

Since retweets involve a relation between two users, the original sender and the retweeting user, we can create a network of such relations for all retweets in the corpus. This retweet graph is shown below.

The retweet graph reveals a large component that is actively involved in retweeting, with smaller star-like components at the fringes. Closer examination reveals that the stars at the fringes were occasional retweeters of famous users (e.g., entertainers) and could easily be identified and excluded from our analysis. The nodes have been drawn in size relative to their in-degree, that is to the degree that their messages had been retweeted, revealing a small number of accounts that rose to prominence in the community.

Zooming in inside this graph reveals the most influential nodes in the community, which we identified as the anonymous citizen reporters. The biggest node belongs to @GodFather.

A closer look at the core of the community reveals 13 nodes that have a larger share of their messages retweeted. The spatial proximity of these nodes determined by a force-directed algorithm indicates that they were also retweeting each other (as opposed to the nodes in the periphery of the retweet graph). The biggest node belongs to @GodFather.

FREQUENCY OF COMMUNICATION

Tweeting activity of three groups of users with different tweeting patterns overlaid with the frequency of appearance for the word “balacera” (shooting). All three groups have an increase in activity, matching the ups of the balacera distribution. There is only one discrepancy, in April-May 2011, related to an event explained in the next section.

WHO DO YOU TRUST?


Daily distribution of tweets for the anonymous account @GodFather and its daily mentions in tweets by other members of the community. In April 2010, he was accused by newly created anonymous accounts of working for the criminal organization. After that event, he decreased his involvement in the community and at the end of July stopped tweeting altogether.

CONCLUSION OR
WHAT DOES IT MEAN TO BE ANONYMOUS IN A DANGEROUS ENVIRONMENT?

In a time when social networking platforms such as Facebook and Google+ are pushing to force users to assume their real-life identities in the Web, we think that it is important to provide examples of communities of citizens for which maintaining their anonymity inside such networks is essential. But being anonymous makes one more susceptible to denigration attacks from other anonymous accounts, leaving the other members of community in the dilemma of who to trust.

Inside a community, even anonymous individuals can establish recognizable identities that they can sustain over time. Such anonymous individuals can become trustworthy if their efforts to serve the interests of the community remain constant over time.


Social Experiments: People vs Machines and In-lab vs Online

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Social Experiments: People vs Machines

Recently, I attended a couple of talks on conducting social experiments. I found them both very interesting for different reasons, and thought of giving you an overview in this posting.

The first talk was at MIT. The Dertouzos lecture was established after the death of MIT’s LCS Director Michael Dertouzos who, even though he left us early, he left behind a great legacy. Given the strong interest of Dertouzos in the inter-disciplinary nature of Computer Science, the choice of Prof. Michael Kearns of UPenn was a particularly appropriate choice. Here is the abstract of Michael’s talk:

“What do the theory of computation, economics and related fields have to say about the emerging phenomena of crowd sourcing and social computing? Most successful applications of crowd sourcing to date have been on problems we might consider “embarrassingly parallelizable” from a computational perspective. But the power of the social computation approach is already evident, and the road cleared for applying it to more challenging problems. In part towards this goal, for a number of years we have been conducting controlled human-subject experiments in distributed social computation in networks with only limited and local communication. These experiments cast a number of traditional computational problems — including graph coloring, consensus, independent set, market equilibria, biased voting and network formation — as games of strategic interaction in which subjects have financial incentives to collectively “compute” global solutions. I will overview and summarize the many behavioral findings from this line of experimentation, and draw broad comparisons to some of the predictions made by the theory of computation and microeconomics.”

Michael is interested in exploring how well would people be able to effectively crowd source in the lab, when presented with a variety of problems, from the computationally easy to the hard. Graph coloring is a hard problem for a computer (i.e., for any parallel or sequential algorithm we know so far). How well would 36 undergraduate students solve instances of graph coloring? Quite well, it turns out. See the video clip.

Finding consensus (e.g., having all nodes in a graph choose the same color) is an easy problem to solve by both sequential and parallel algorithms. Yet, when presented with a time limit, humans have troubles reaching consensus as they are not able to come up consistently with a successful strategy: some will change colors often, trying to accommodate their neighbors; others will stick stubbornly to their color expecting other to follow them, yet others will flip-flop a lot giving up at the wrong moment, etc. Experience does not seem to help: Playing this game over and over, seems to be teaching them little. See this video clip of 36 undergraduates finding consensus of a graph composed of highly interconnected tribes.

The two video clips I recorded on my iPad during his talk are only a small teaser of the work Michael Kearns presented. If you are interested, you should take a closer look at his published papers.

Social experiments in the lab vs online

The second talk was at the Berkman Center for Internet and Society. Fellow Jerome Hergueux’s talk was entitled “The Promises of Web-based Social Experiments.” He is interested in exploring how closely the results of experiments conducted online match those conducted in the lab. Here is the abstract of his talk:

“The advent of the internet provides social scientists with a fantastic tool for conducting behavioral experiments online at a very large-scale and at an affordable cost. It is surprising, however, how little research has leveraged the affordances of the internet to set up such social experiments so far.  In this talk, Jerome Hergueux will introduce the audience to one of the first online platforms specifically designed for conducting interactive social experiments over the internet to date. He will present the preliminary results of a randomized experiment that compares behavioral measures of social preferences obtained both in a traditional University laboratory and online, with a focus on engaging the audience in a reflection about the specificities, limitations and promises of online experimental economics as a tool for social science research”

Jerome and his colleagues at the University of Paris tried to re-create online as close as possible the environment of the labs that social scientists have used for a long time. They recruited subjects from the very same pool, and asked some of them to participate in experiments in a lab setting, while others were to participate in the very same experiments online. There were no interactions between the participants, though the ones in the lab would see who else had come for the experiments. What they found was that the results of the experiments differ! In particular they found that the online subjects seem to be significantly more social than those in the Lab: More altruistic, showing higher trust, and being less risk averse. While this is still preliminary work, it seems quite promising in giving us a better understanding on the transformation we undergo when we go online. You can watch the full talk of Jerome Hergueux from the Berkman’s site.

We still have a lot to learn about conducting social experiments, but these two talks are definitely helping in this direction.

 

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