Should online communities require people to create accounts before participating?
This question has been a source of disagreement among people who start or manage online communities for decades. Requiring accounts makes some sense since users contributing without accounts are a common source of vandalism, harassment, and low quality content. In theory, creating an account can deter these kinds of attacks while still making it pretty quick and easy for newcomers to join. Also, an account requirement seems unlikely to affect contributors who already have accounts and are typically the source of most valuable contributions. Creating accounts might even help community members build deeper relationships and commitments to the group in ways that lead them to stick around longer and contribute more.
In a new paper published in Communication Research, Benjamin Mako Hill and Aaron Shaw provide an answer. We analyze data from “natural experiments” that occurred when 136 wikis on Fandom.com started requiring user accounts. Although we find strong evidence that the account requirements deterred low quality contributions, this came at a substantial (and usually hidden) cost: a much larger decrease in high quality contributions. Surprisingly, the cost includes “lost” contributions from community members who had accounts already, but whose activity appears to have been catalyzed by the (often low quality) contributions from those without accounts.
The full citation for the paper is: Hill, Benjamin Mako, and Aaron Shaw. 2020. “The Hidden Costs of Requiring Accounts: Quasi-Experimental Evidence from Peer Production.” Communication Research, 48 (6): 771–95. https://doi.org/10.1177/0093650220910345.
In exciting collective news, the US National Science Foundation announced that Benjamin Mako Hill has received of one of this year’s CAREER awards. The CAREER is the most prestigious grant that the NSF gives to early career scientists in all fields.
Like everyone else, Internet users who protect their privacy by using the anonymous browsing software Tor are welcome to read Wikipedia. However, when Tor users try to contribute to the self-described “encyclopedia that anybody can edit,” they typically come face-to-face with a notice explaining that their participation is not welcome.
Our new paper—led by Chau Tran at NYU and authored by a group of researchers from the University of Washington, the Community Data Science Collective, Drexel, and New York University—was published and presented this week at the IEEE Symposium on Security & Privacy and provides insight into what Wikipedia might be missing out on by blocking Tor. By comparing contributions from Tor that slip past Wikipedia’s ban to edits made by other types of contributors, we find that Tor users make contributions to Wikipedia that are just as valuable as those made by new and unregistered Wikipedia editors. We also found that Tor users are more likely to engage with certain controversial topics.
To conduct our study, we first identified more than 11,000 Wikipedia edits made by Tor users who were able to bypass Wikipedia’s ban on contributions from Tor between 2007 and 2018. We then used a series of quantitative techniques to evaluate the quality of these contributions. We found that Tor users made contributions that were similar in quality to, and in some senses even better than, contributions made by other users without accounts and newcomers making their first edits.
We used a range of analytical techniques including direct parsing of article histories, manual inspections of article changes, and a machine learning platform called ORES to analyze contributions. We also used a machine learning technique called topic modeling to analyze Tor users’ areas of interest by checking their edits against clusters of keywords. We found that Tor-based editors are more likely than other users to focus on topics that may be considered controversial, such as politics, technology, and religion.
In a closely connected study led by Kaylea Champion and published several months ago in the Proceedings of the ACM on Human Computer Interaction (CSCW), we conducted a forensic qualitative analysis of contributions of the same dataset. Our results in that study are described in a separate blog post about that project and paint a complementary picture of Tor users engaged—in large part—in uncontroversial and quotidian types of editing behavior.
Across the two papers, our results are similar to other work that suggests that Tor users are very similar to other internet users. For example, one previous study has shown that Tor users frequently visit websites in the Alexa top one million.
Much of the discourse about anonymity online tends toward extreme claims backed up by very little in the way of empirical evidence or systematic study. Our work is a step toward remedying this gap and has implications for many websites that limit participation by users of anonymous browsing software like Tor. In the future, we hope to conduct similar systematic studies in contexts beyond Wikipedia.
In terms of Wikipedia’s own policy decisions about anonymous participation, we believe that our paper suggests that the benefits of a “pathway to legitimacy” for Tor contributors to Wikipedia might exceed the potential harm due to the value of their contributions. We are particularly excited about exploring ways to allow contributors from anonymity-seeking users under certain conditions: for example, requiring review prior to changes going live. Of course, these are questions for the Wikipedia community to decide but it’s a conversation that we hope our research can inform and that we look forward to participating in.
Paper Citation: Tran, Chau, Kaylea Champion, Andrea Forte, Benjamin Mako Hill, and Rachel Greenstadt. “Are Anonymity-Seekers Just like Everybody Else? An Analysis of Contributions to Wikipedia from Tor.” In 2020 IEEE Symposium on Security and Privacy (SP), 1:974–90. San Francisco, California: IEEE Computer Society, 2020. https://doi.org/10.1109/SP40000.2020.00053.
In May 2019, we were invited to give short remarks on the impact of Janet Fulk and Peter Monge at the International Communication Association‘s annual meeting as part of a session called “Igniting a TON (Technology, Organizing, and Networks) of Insights: Recognizing the Contributions of Janet Fulk and Peter Monge in Shaping the Future of Communication Research.”
Mako Hill gave a four-minute talk on Janet and Peter’s impact to the work of the Community Data Science Collective. Mako unpacked some of the cryptic acronyms on the CDSC-UW lab’s whiteboard as well as explaining that our group has a home in the academic field of communication, in no small part, because of the pioneering scholarship of Janet and Peter. You can view the talk in WebM or on Youtube.
The conference marks the official publication of four papers by collective students and faculty. All four papers were published in the journal Proceedings of the ACM on Human-Computer Interaction: CSCW.
Information on the talks as well as links to the papers are available here (CSCW members are listed in italics):
Mon, Nov 11 14:30 – 16:00: A Forensic Qualitative Analysis of Contributions to Wikipedia from Anonymity-Seeking Users by Kaylea Champion (UW), Nora McDonald (Drexel), Stephanie E Bankes (Drexel), Joseph Zhang (Drexel), Rachel Greenstadt (NYU), Andrea Forte (Drexel), Benjamin Mako Hill (UW). Kaylea will present! [Paper]
Mon, Nov 11 14:30 – 16:00: Wikipedia and Wiki Research
Salt, Kaylea, Charlie, Regina, and Kaylea will all be at the conference as will affiliate Andrés Monroy-Hernández and tons of our social computing friends. Please come and say “Hello” to any of us, introduce yourself if you don’t already know us, and pick up a CDSC sticker!
Online anonymity often gets a bad rap and complaints about antisocial behavior from anonymous Internet users are as old as the Internet itself. On the other hand, research has shown that many Internet users seek out anonymity to protect their privacy while contributing things of value. Should people seeking to contribute to open collaboration projects like open source software and citizen science projects be required to give up identifying information in order to participate?
We conducted a two-part study to better understand how open collaboration projects balance the threats of bad behavior with the goal of respecting contributors’ expectations of privacy. First, we interviewed eleven people from five different open collaboration “service providers” to understand what threats they perceive to their projects’ mission and how these threats shape privacy and security decisions when it comes to anonymous contributions. Second, we analyzed discussions about anonymous contributors on publicly available logs of the English language Wikipedia mailing list from 2010 to 2017.
In the interview study, we identified three themes that pervaded discussions of perceived threats. These included threats to:
community norms, such as harrassment;
sustaining participation, such as loss of or failure to attract volunteers; and
contribution quality, low-quality contributions drain community resources.
We found that open collaboration providers were most concerned with lowering barriers to participation to attract new contributors. This makes sense given that newbies are the lifeblood of open collaboration communities. We also found that service providers thought of anonymous contributions as a way of offering low barriers to participation, not as a way of helping contributors manage their privacy. They imagined that anonymous contributors who wanted to remain in the community would eventually become full participants by registering for an account and creating an identity on the site. This assumption was evident in policies and technical features of collaboration platforms that barred anonymous contributors from participating in discussions, receiving customized suggestions, or from contributing at all in some circumstances. In our second study of the English language Wikipedia public email listserv, we discovered that the perspectives we encountered in interviews also dominated discussions of anonymity on Wikipedia. In both studies, we found that anonymous contributors were seen as “second-class citizens.”
This is not the way anonymous contributors see themselves. In a study we published two years ago, we interviewed people who sought out privacy when contributing to open collaboration projects. Our subjects expressed fears like being doxed, shot at, losing their job, or harassed. Some were worried about doing or viewing things online that violated censorship laws in their home country. The difference between the way that anonymity seekers see themselves and the way they are seen by service providers was striking.
One cause of this divergence in perceptions around anonymous contributors uncovered by our new paper is that people who seek out anonymity are not able to participate fully in the process of discussing and articulating norms and policies around anonymous contribution. People whose anonymity needs means they cannot participate in general cannot participate in the discussions that determine who can participate.
We conclude our paper with the observation that, although social norms have played an important role in HCI research, relying on them as a yardstick for measuring privacy expectations may leave out important minority experiences whose privacy concerns keep them from participating in the first place. In online communities like open collaboration projects, social norms may best reflect the most privileged and central users of a system while ignoring the most vulnerable
Both this blog post and the paper, Privacy, Anonymity, and Perceived Risk in Open Collaboration: A Study of Service Providers, was written by Nora McDonald, Benjamin Mako Hill, Rachel Greenstadt, and Andrea Forte and will be published in the Proceedings of the 2019 ACM CHI Conference on Human Factors in Computing Systems next week. The paper will be presented at the CHI conference in Glasgow, UK on Wednesday May 8, 2019. The work was supported by the National Science Foundation (awards CNS-1703736 and CNS-1703049).
I’ve heard a surprising “fact” repeated in the CHI and CSCW communities that receiving a best paper award at a conference is uncorrelated with future citations.
Although it’s surprising and counterintuitive, it’s a nice thing to
think about when you don’t get an award and its a nice thing to say to
others when you do. I’ve thought it and said it myself.
It also seems to be untrue. When I tried to check the “fact”
recently, I found a body of evidence that suggests that computing papers
that receive best paper awards are, in fact, cited more often than
papers that do not.
The source of the original “fact” seems to be a CHI 2009 study by Christoph Bartneck and Jun Hu titled “Scientometric Analysis of the CHI Proceedings.”
Among many other things, the paper presents a null result for a test of
a difference in the distribution of citations across best papers
awardees, nominees, and a random sample of non-nominees.
Although the award analysis is only a small part of Bartneck and Hu’s
paper, there have been at least two papers have have subsequently
brought more attention, more data, and more sophisticated analyses to
the question. In 2015, the question was asked by Jaques Wainer, Michael
Eckmann, and Anderson Rocha in their paper “Peer-Selected ‘Best Papers’—Are They Really That ‘Good’?“
Wainer et al. build two datasets: one of papers from 12 computer
science conferences with citation data from Scopus and another papers
from 17 different conferences with citation data from Google Scholar.
Because of parametric concerns, Wainer et al. used a non-parametric
rank-based technique to compare awardees to non-awardees. Wainer et al.
summarize their results as follows:
The probability that a best paper
will receive more citations than a non best paper is 0.72 (95% CI =
0.66, 0.77) for the Scopus data, and 0.78 (95% CI = 0.74, 0.81) for the
Scholar data. There are no significant changes in the probabilities for
different years. Also, 51% of the best papers are among the top 10% most
cited papers in each conference/year, and 64% of them are among the top
20% most cited.
Lee looked at 43,000 papers from 81 conferences and built a
regression model to predict citations. Taking into an account a number
of controls not considered in previous analyses, Lee finds that the
marginal effect of receiving a best paper award on citations is
positive, well-estimated, and large.
Why did Bartneck and Hu come to such a different conclusions than later work?
My first thought was that perhaps CHI is different than the rest of
computing. However, when I looked at the data from Bartneck and Hu’s
2009 study—conveniently included as a figure in their original study—you
can see that they did find a higher mean among the award
recipients compared to both nominees and non-nominees. The entire
distribution of citations among award winners appears to be pushed
upwards. Although Bartneck and Hu found an effect, they did not find a statistically significant effect.
Given the more recent work by Wainer et al. and Lee, I’d be willing
to venture that the original null finding was a function of the fact
that citations is a very noisy measure—especially over a 2-5
post-publication period—and that the Bartneck and Hu dataset was small
with only 12 awardees out of 152 papers total. This might have caused
problems because the statistical test the authors used was an omnibus
test for differences in a three-group sample that was imbalanced heavily
toward the two groups (nominees and non-nominees) in which their
appears to be little difference. My bet is that the paper’s conclusions
on awards is simply an example of how a null effect is not evidence of a
non-effect—especially in an underpowered dataset.
Of course, none of this means that award winning papers are better.
Despite Wainer et al.’s claim that they are showing that award winning
papers are “good,” none of the analyses presented can disentangle the
signalling value of an award from differences in underlying paper
quality. The packed rooms one routinely finds at best paper sessions at
conferences suggest that at least some additional citations received by
award winners might be caused by extra exposure caused by the awards
themselves. In the future, perhaps people can say something along these
lines instead of repeating the “fact” of the non-relationship.
Couchsurfing and Airbnb are websites that connect people with an extra guest room or couch with random strangers on the Internet who are looking for a place to stay. Although Couchsurfing predates Airbnb by about five years, the two sites are designed to help people do the same basic thing and they work in extremely similar ways. They differ, however, in one crucial respect. On Couchsurfing, the exchange of money in return for hosting is explicitly banned. In other words, couchsurfing only supports the social exchange of hospitality. On Airbnb, users must use money: the website is a market on which people can buy and sell hospitality.
The figure above compares the number of people with at least some trust or verification on both Couchsurfing and Airbnb based on when each user signed up. The picture, as I have argued elsewhere, reflects a broader pattern that has occurred on the web over the last 15 years. Increasingly, social-based systems of production and exchange, many like Couchsurfing created during the first decade of the Internet boom, are being supplanted and eclipsed by similar market-based players like Airbnb.
In a paper led by Max Klein that was recently published and will be presented at the ACM Conference on Computer-supported Cooperative Work and Social Computing (CSCW) which will be held in Jersey City in early November 2018, we sought to provide a window into what this change means and what might be at stake. At the core of our research were a set of interviews we conducted with “dual-users” (i.e. users experienced on both Couchsurfing and Airbnb). Analyses of these interviews pointed to three major differences, which we explored quantitatively from public data on the two sites.
First, we found that users felt that hosting on Airbnb appears to require higher quality services than Couchsurfing. For example, we found that people who at some point only hosted on Couchsurfing often said that they did not host on Airbnb because they felt that their homes weren’t of sufficient quality. One participant explained that:
“I always wanted to host on Airbnb but I didn’t actually have a bedroom that I felt would be sufficient for guests who are paying for it.”
An another interviewee said:
“If I were to be paying for it, I’d expect a nice stay. This is why I never Airbnb-hosted before, because recently I couldn’t enable that [kind of hosting].”
We conducted a quantitative analysis of rates of Airbnb and Couchsurfing in different cities in the United States and found that median home prices are positively related to number of per capita Airbnb hosts and a negatively related to the number of Couchsurfing hosts. Our exploratory models predicted that for each $100,000 increase in median house price in a city, there will be about 43.4 more Airbnb hosts per 100,000 citizens, and 3.8 fewer hosts on Couchsurfing.
A second major theme we identified was that, while Couchsurfing emphasizes people, Airbnb places more emphasis on places. One of our participants explained:
“People who go on Airbnb, they are looking for a specific goal, a specific service, expecting the place is going to be clean […] the water isn’t leaking from the sink. I know people who do Couchsurfing even though they could definitely afford to use Airbnb every time they travel, because they want that human experience.”
In a follow-up quantitative analysis we conducted of the profile text from hosts on the two websites with a commonly-used system for text analysis called LIWC, we found that, compared to Couchsurfing, a lower proportion of words in Airbnb profiles were classified as being about people while a larger proportion of words were classified as being about places.
Finally, our research suggested that although hosts are the powerful parties in exchange on Couchsurfing, social power shifts from hosts to guests on Airbnb. Reflecting a much broader theme in our interviews, one of our participants expressed this concisely, saying:
“On Airbnb the host is trying to attract the guest, whereas on Couchsurfing, it works the other way round. It’s the guest that has to make an effort for the host to accept them.”
Previous research on Airbnb has shown that guests tend to give their hosts lower ratings than vice versa. Sociologists have suggested that this asymmetry in ratings will tend to reflect the direction of underlying social power balances.
We both replicated this finding from previous work and found that, as suggested in our interviews, the relationship is reversed on Couchsurfing. As shown in the figure above, we found Airbnb guests will typically give a less positive review to their host than vice-versa while in Couchsurfing guests will typically a more positive review to the host.
As Internet-based hospitality shifts from social systems to the market, we hope that our paper can point to some of what is changing and some of what is lost. For example, our first result suggests that less wealthy participants may be cut out by market-based platforms. Our second theme suggests a shift toward less human-focused modes of interaction brought on by increased “marketization.” We see the third theme as providing somewhat of a silver-lining in that shifting power toward guests was seen by some of our participants as a positive change in terms of safety and trust in that guests. Travelers in unfamiliar places often are often vulnerable and shifting power toward guests can be helpful.
Although our study is only of Couchsurfing and Airbnb, we believe that the shift away from social exchange and toward markets has broad implications across the sharing economy. We end our paper by speculating a little about the generalizability of our results. I have recently spoken at much more length about the underlying dynamics driving the shift we describe in my recent LibrePlanet keynote address.
Every CASBS study is labeled with a list of “ghosts” who previously occupied the study. This year, I’m spending the year in Study 50 where I’m haunted by an incredible cast that includes many people whose scholarship has influenced and inspired me.
Foremost among this group is Study 50’s third occupant: Claude Shannon.¹
At 21 years old, Shannon’s masters thesis (sometimes cited as the most important masters thesis in history) proved that electrical circuits could encode any relationship expressible in Boolean logic and opened the door to digital computing. Incredibly, this is almost never cited as Shannon’s most important contribution. That came in 1948 when he published a paper titled A Mathematical Theory of Communication which effectively created the field of information theory. Less than a decade after its publication, Aleksandr Khinchin (the mathematician behind my favorite mathematical constant) described the paper saying:
Rarely does it happen in mathematics that a new discipline achieves the character of a mature and developed scientific theory in the first investigation devoted to it…So it was with information theory after the work of Shannon.
As someone whose own research is seeking to advance computation and mathematical study of communication, I find it incredibly propitious to be sharing a study with Shannon.
Although I teach in a communication department, I know Shannon from my background in computing. I’ve always found it curious that, despite the fact Shannon’s 1948 paper is almost certainly the most important single thing ever published with the word “communication” in its title, Shannon is rarely taught in communication curricula is sometimes completely unknown to communication scholars.
In establishing itself under the banner of communication, the discipline staked an academic claim to the entire field of communication theory and research—a very big claim indeed, since communication had already been widely studied and theorized. Peters writes that communication research became “an intellectual Taiwan-claiming to be all of China when, in fact, it was isolated on a small island” (p. 545). Perhaps the most egregious case involved Shannon’s mathematical theory of information (Shannon & Weaver, 1948), which communication scholars touted as evidence of their field’s potential scientific status even though they had nothing whatever to do with creating it, often poorly understood it, and seldom found any real use for it in their research.
In preparation for moving into Study 50, I read a new biography of Shannon by Jimmy Soni and Rob Goodman and was excited to find that Craig—although accurately describing many communication scholars’ lack of familiarity—almost certainly understated the importance of Shannon to communication scholarship.
For example, the book form of Shannon’s 1948 article was published by University Illinois on the urging of and editorial supervision of Wilbur Schramm (one of the founders of modern mass communication scholarship) who was a major proponent of Shannon’s work. Everett Rogers (another giant in communication) devotes a chapter of his “History of Communication Studies”² to Shannon and to tracing his impact in communication. Both Schramm and Rogers built on Shannon in parts of their own work. Shannon has had an enormous impact, it turns out, in several subareas of communication research (e.g., attempts to model communication processes).
Although I find these connections exciting. My own research—like most of the rest of communication—is far from the substance of technical communication processes at the center of Shannon’s own work. In this sense, it can be a challenge to explain to my colleagues in communication—and to my fellow CASBS fellows—why I’m so excited to be sharing a space with Shannon this year.
Upon reflection, I think it boils down to two reasons:
Shannon’s work is both mathematically beautiful and incredibly useful. His seminal 1948 article points to concrete ways that his theory can be useful in communication engineering including in compression, error correcting codes, and cryptography. Shannon’s focus on research that pushes forward the most basic type of basic research while remaining dedicated to developing solutions to real problems is a rare trait that I want to feature in my own scholarship.
Shannon was incredibly playful. Shannon played games, juggled constantly, and was always seeking to teach others to do so. He tinkered, rode unicycles, built a flame-throwing trumpet, and so on. With Marvin Minsky, he invented the “ultimate machine”—a machine that’s only function is to turn itself off—which he kept on his desk.
I have no misapprehension that I will accomplish anything like Shannon’s greatest intellectual achievements during my year at CASBS. I do hope to be inspired by Shannon’s creativity, focus on impact, and playfulness. In my own little ways, I hope to build something at CASBS that will advance mathematical and computational theory in communication in ways that Shannon might have appreciated.
Incredibly, the year that Shannon was in Study 50, his neighbor in Study 51 was Milton Friedman. Two thoughts: (i) Can you imagine?! (ii) I definitely chose the right study!
Rogers book was written, I found out, during his own stint at CASBS. Alas, it was not written in Study 50.