Adam D. I. Kramer

A 61-Million-Person Experiment in Social Influence and Political Mobilization

Human behaviour is thought to spread through face-to-face social networks, but it is difficult to identify social influence effects in observational studies, and it is unknown whether online social networks operate in the same way–. Here we report results from a randomized controlled trial of political mobilization messages delivered to 61 million Facebook users during the 2010 US congressional elections. The results show that the messages directly influenced political self-expression, information seeking and real-world voting behaviour of millions of people. Furthermore, the messages not only influenced the users who received them but also the users’ friends, and friends of friends. The effect of social transmission on real-world voting was greater than the direct effect of the messages themselves, and nearly all the transmission occurred between ‘close friends’ who were more likely to have a face-to-face relationship. These results suggest that strong ties are instrumental for spreading both online and real-world behaviour in human social networks.

Detecting emotional contagion in massive social networks

Happiness and other emotions spread between people in direct contact, but it is unclear whether massive online social networks also contribute to this spread. Here, we elaborate a novel method for measuring the contagion of emotional expression. With data from millions of Facebook users, we show that rainfall directly influences the emotional content of their status messages, and it also affects the status messages of friends in other cities who are not experiencing rainfall. For every one person affected directly, rainfall alters the emotional expression of about one to two other people, suggesting that online social networks may magnify the intensity of global emotional synchrony.

The spread of emotion via facebook

In this paper we study large-scale emotional contagion through an examination of Facebook status updates. After a user makes a status update with emotional content, their friends are significantly more likely to make a valence-consistent post. This effect is significant even three days later, and even after controlling for prior emotion expressions by both users and their friends. This indicates not only that emotional contagion is possible via text-only communication and that emotions flow through social networks, but also that emotion spreads via indirect communications media.

Using linguistic features to measure presence in computer-mediated communication

We propose a method of measuring peoples sense of presence in computer-mediated communication (CMC) systems) based on linguistic features of their dialogues. We create variations in presence by asking participants to collaborate on physical tasks in four CMC conditions. We then correlate self-reported feelings of presence with the use of specific linguistic features. Regression analyses show that 30% of the variance in self-reported presence can be accounted for by a small number of task-independent linguistic features. Even better prediction can be obtained when self-reported coordination is added to the regression equation. We conclude that linguistic measures of presence have value for studies of CMC.

Facebook for health: opportunities and challenges for driving behavior change

Obesity, mood, and associated behaviors spread within social networks [1]. Facebook, the primary representation of these networks, shapes our perceptions of social norms and the expectations we set for ourselves. As such, Facebook holds potential to influence health behaviors of individuals and improve public health. This panel explores that potential from a variety of perspectives including psychology, public health, privacy, and design innovation. Panelists include: Margie Morris and Sunny Consolvo, researchers at Intel who have created novel mobile health and Facebook applications; Sean Munson, a social computing researcher at University of Michigan; Kevin Patrick, of UCSD, who is investigating social media for preventing and reducing weight gain in young adults; and Janice Tsai, from Microsoft, who focuses on privacy implications of Facebook. This panel will identify opportunities for health interventions on Facebook to have a broad social impact, challenges to implementing effective interventions on this dynamic platform, appropriate research methods, and considerations related to privacy and ethics.

Autism online: a comparison of word usage in bloggers with and without autism spectrum disorders

The Internet has become a place of refuge for individuals with autism spectrum disorders (ASD). In particular, weblogs are a popular option for personal expression via the Internet. Perhaps this means of communication is well suited to bypassing deficits in social interaction and communication that characterize ASD. Using the Linguistic Inquiry and Word Count (LIWC) dictionaries [10], we compared blogs of individuals with ASD to the writing of neurotypical (NT) bloggers. We found that rates of word usage were nearly identical in the two groups with one exception - there was more variation in the use of social words in ASD compared to NT blogs. This similarity in language between ASD and NT authors suggests that communication deficits routinely found in people with ASD may be due to the social context in which their communication skills are tested, and that the affordances of asynchronous computer-mediated communication may offer alternative means of testing and expression.

Word usage and posting behaviors: modeling blogs with unobtrusive data collection methods

We present a large-scale analysis of the content of weblogs dating back to the release of the Blogger program in 1999. Over one million blogs were analyzed from their conception through June 2006. These data was submitted to the Text Analysis: Word Counts program [12], which conducted a word-count analysis using Linguistic Inquiry and Word Counts (LIWC) dictionaries [20] to provide and analyze a representative sample of blogger word usage. Covariation among LIWC dictionaries suggests that blogs vary along five psychologically relevant linguistic dimensions: Melancholy, Socialness, Ranting, Metaphysicality, and Work-Relatedness. These variables and others were subjected to a cluster analysis in an attempt to extract natural usage groups to inform design of blogging systems, the results of which were mixed.

Yahtzee: An Anonymized Group Level Matching Procedure

Researchers often face the problem of needing to protect the privacy of subjects while also needing to integrate data that contains personal information from diverse data sources. The advent of computational social science and the enormous amount of data about people that is being collected makes protecting the privacy of research subjects ever more important. However, strict privacy procedures can hinder the process of joining diverse sources of data that contain information about specific individual behaviors. In this paper we present a procedure to keep information about specific individuals from being “leaked” or shared in either direction between two sources of data without need of a trusted third party. To achieve this goal, we randomly assign individuals to anonymous groups before combining the anonymized information between the two sources of data. We refer to this method as the Yahtzee procedure, and show that it performs as predicted by theoretical analysis when we apply it to data from Facebook and public voter records.