online_experiments   16

Investigator Characteristics and Respondent Behavior in Online Surveys | Journal of Experimental Political Science | Cambridge Core
Prior research demonstrates that responses to surveys can vary depending on the race, gender, or ethnicity of the investigator asking the question. We build upon this research by empirically testing how information about researcher identity in online surveys affects subject responses. We do so by conducting an experiment on Amazon’s Mechanical Turk in which we vary the name of the researcher in the advertisement for the experiment and on the informed consent page in order to cue different racial and gender identities. We fail to reject the null hypothesis that there is no difference in how respondents answer questions when assigned to a putatively black/white or male/female researcher.
online_experiments  amazon_turk  survey  race  gender  bias  sociology_of_science  social_psychology  via:nyhan 
march 2018 by rvenkat
Social Influence and Reciprocity in Online Gift Giving – Facebook Research
Giving gifts is a fundamental part of human relationships that is being affected by technology. The Internet enables people to give at the last minute and over long distances, and to observe friends giving and receiving gifts. How online gift giving spreads in social networks is therefore important to understand. We examine 1.5 million gift exchanges on Facebook and show that receiving a gift causes individuals to be 56% more likely to give a gift in the future. Additional surveys show that online gift giving was more socially acceptable to those who learned about it by observing friends’ participation instead of a non-social encouragement. Most receivers pay the gift forward instead of reciprocating directly online, although surveys revealed additional instances of direct reciprocity, where the initial gifting occurred offline. Thus, social influence promotes the spread of online gifting, which both complements and substitutes for offline gifting.

-- something about facebook experiments and the magnitude of intervention effects make me suspicious. Maybe, I'm to reading too many of Gelman's posts.
norms  influence  contagion  online_experiments  observational_studies  social_networks  networks  teaching  i_remain_skeptical 
march 2018 by rvenkat
The Polarizing Effects of Online Partisan Criticism: Evidence from Two ExperimentsThe International Journal of Press/Politics - Elizabeth Suhay, Emily Bello-Pardo, Brianna Maurer, 2018
Affective and social political polarization—a dislike of political opponents and a desire to avoid their company—are increasingly salient and pervasive features of politics in many Western democracies, particularly the United States. One contributor to these related phenomena may be increasing exposure to online political disagreements in which ordinary citizens criticize, and sometimes explicitly demean, opponents. This article presents two experimental studies that assessed whether U.S. partisans’ attitudes became more prejudiced in favor of the in-party after exposure to online partisan criticism. In the first study, we draw on an online convenience sample to establish that partisan criticism that derogates political opponents increases affective polarization. In the second, we replicate these findings with a quasi-representative sample and extend the pattern of findings to social polarization. We conclude that online partisan criticism likely has contributed to rising affective and social polarization in recent years between Democrats and Republicans in the United States, and perhaps between partisan and ideological group members in other developed democracies as well. We close by discussing the troubling implications of these findings in light of continuing attempts by autocratic regimes and other actors to influence democratic elections via false identities on social media.
political_science  online_experiments  polarization  democracy  partyism  us_politics  via:nyhan  dmce  teaching 
december 2017 by rvenkat
Complex Thinking as a Result of Incongruent Information ExposureAmerican Politics Research - Cengiz Erisen, Dave Redlawsk, Elif Erisen, 2017
In this article, we explore whether incongruent information influences what people recall to mind about a presidential candidate’s policy statements. We investigate whether the volume of people’s political thoughts, their ability to produce arguments, the affective valence of these thoughts, and their integrative complexity are influenced by the congruency between new political information and prior political convictions. We conducted an experiment via MTurk manipulating the congruency of information with respect to ideology. Our results show that incongruency significantly alters how people think about politics. Incongruent information increases integrative complexity of the opposing thoughts, becomes more voluminous, and includes more rationales. Moreover, these defensive thoughts are significantly more negative and less positive about the incongruent information. Parallel to what studies on motivated reasoning demonstrated, we also find that politically knowledgeable people in particular seem to strengthen their thoughts’ cognitive structure while defending their priors against information counter to their political views. We further discuss the general effects of these results and the importance of challenges to existing beliefs in generating complex thought systems.

-- can these domain specific findings generalize well?
public_opinion  political_psychology  cultural_cognition  ideology  heuristics  dmce  teaching  amazon_turk  online_experiments  via:nyhan 
november 2017 by rvenkat
Social influence and political mobilization: Further evidence from a randomized experiment in the 2012 U.S. presidential election
A large-scale experiment during the 2010 U.S. Congressional Election demonstrated a positive effect of an online get-out-the-vote message on real world voting behavior. Here, we report results from a replication of the experiment conducted during the U.S. Presidential Election in 2012. In spite of the fact that get-out-the-vote messages typically yield smaller effects during high-stakes elections due to saturation of mobilization efforts from many sources, a significant increase in voting was again observed. Voting also increased significantly among the close friends of those who received the message to go to the polls, and the total effect on the friends was likely larger than the direct effect, suggesting that understanding social influence effects is potentially even more important than understanding the direct effects of messaging. These results replicate earlier work and they add to growing evidence that online social networks can be instrumental for spreading offline behaviors.
networked_life  network_data_analysis  online_experiments  intervention  political_science  social_networks  networks  teaching 
september 2017 by rvenkat
VoxPL: Programming with the Wisdom of the Crowd - Microsoft Research
Having a crowd estimate a numeric value is the original inspiration for the notion of “the wisdom of the crowd.” Quality control for such estimated values is challenging because prior, consensus-based approaches for quality control in labeling tasks are not applicable in estimation tasks. We present

We present VOXPL, a high-level programming framework that automatically obtains high-quality crowdsourced estimates of values. The VOXPL domain-specific language lets programmers concisely specify complex estimation tasks with a desired level of confidence and budget. VOXPL’s runtime system implements a novel quality control algorithm that automatically computes sample sizes and obtains high-quality estimates from the crowd at low cost. To evaluate VOXPL, we implement four estimation applications, ranging from facial feature recognition to calorie counting. The resulting programs are concise—under 200 lines of code—and obtain high-quality estimates from the crowd quickly and inexpensively.
online_experiments  collective_cognition  crowd_sourcing  amazon_turk  software 
april 2017 by rvenkat
[1608.01987] Human collective intelligence as distributed Bayesian inference
Collective intelligence is believed to underly the remarkable success of human society. The formation of accurate shared beliefs is one of the key components of human collective intelligence. How are accurate shared beliefs formed in groups of fallible individuals? Answering this question requires a multiscale analysis. We must understand both the individual decision mechanisms people use, and the properties and dynamics of those mechanisms in the aggregate. As of yet, mathematical tools for such an approach have been lacking. To address this gap, we introduce a new analytical framework: We propose that groups arrive at accurate shared beliefs via distributed Bayesian inference. Distributed inference occurs through information processing at the individual level, and yields rational belief formation at the group level. We instantiate this framework in a new model of human social decision-making, which we validate using a dataset we collected of over 50,000 users of an online social trading platform where investors mimic each others' trades using real money in foreign exchange and other asset markets. We find that in this setting people use a decision mechanism in which popularity is treated as a prior distribution for which decisions are best to make. This mechanism is boundedly rational at the individual level, but we prove that in the aggregate implements a type of approximate "Thompson sampling"---a well-known and highly effective single-agent Bayesian machine learning algorithm for sequential decision-making. The perspective of distributed Bayesian inference therefore reveals how collective rationality emerges from the boundedly rational decision mechanisms people use.

:(
bayesian  cognition  collective_cognition  joshua.tenenbaum  online_experiments  i_remain_skeptical 
december 2016 by rvenkat
[1507.08863] Keeping up with the e-Joneses: Do online social networks raise social comparisons?
Online social networks such as Facebook disclose an unprecedented volume of personal information amplifying the occasions for social comparisons. We test the hypothesis that the use of social networking sites (SNS) increases people's dissatisfaction with their income. After addressing endogeneity issues, our results suggest that SNS users have a higher probability to compare their achievements with those of others. This effect seems stronger than the one exerted by TV watching, it is particularly strong for younger people, and it affects men and women in a similar way.
online_experiments  homophily  sociology  social_networks 
august 2015 by rvenkat
[1507.07632] Geography of Emotion: Where in a City are People Happier?
Location-sharing services were built upon people's desire to share their activities and locations with others. By "checking-in" to a place, such as a restaurant, a park, gym, or train station, people disclose where they are, thereby providing valuable information about land use and utilization of services in urban areas. This information may, in turn, be used to design smarter, happier, more equitable cities. We use data from Foursquare location-sharing service to identify areas within a major US metropolitan area with many check-ins, i.e., areas that people like to use. We then use data from the Twitter microblogging platform to analyze the properties of these areas. Specifically, we have extracted a large corpus of geo-tagged messages, called tweets, from a major metropolitan area and linked them US Census data through their locations. This allows us to measure the sentiment expressed in tweets that are posted from a specific area, and also use that area's demographic properties in analysis. Our results reveal that areas with many check-ins are different from other areas within the metropolitan region. In particular, these areas have happier tweets, which also encourage people from other areas to commute longer distances to these places. These findings shed light on human mobility patterns, as well as how physical environment influences human emotions.
sentiment_analysis  online_experiments  subjective_well-being 
august 2015 by rvenkat

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