Characterizing Attention Cascades in WhatsApp Groups

An important political and social phenomena discussed in several countries, like India and Brazil, is the use of WhatsApp to spread false or misleading content. However, little is known about the information dissemination process in WhatsApp groups. Attention affects the dissemination of information in WhatsApp groups, determining what topics or subjects are more attractive to participants of a group. In this paper, we characterize and analyze how attention propagates among the participants of a WhatsApp group. An attention cascade begins when a user asserts a topic in a message to the group, which could include written text, photos, or links to articles online. Others then propagate the information by responding to it. We analyzed attention cascades in more than 1.7 million messages posted in 120 groups over one year. Our analysis focused on the structural and temporal evolution of attention cascades as well as on the behavior of users that participate in them. We found specific characteristics in cascades associated with groups that discuss political subjects and false information. For instance, we observe that cascades with false information tend to be deeper, reach more users, and last longer in political groups than in non-political groups.Comment: Accepted as a full paper at the 11th International ACM Web Science Conference (WebSci 2019). Please cite the WebSci versio

DeepInf: Social Influence Prediction with Deep Learning

Social and information networking activities such as on Facebook, Twitter, WeChat, and Weibo have become an indispensable part of our everyday life, where we can easily access friends' behaviors and are in turn influenced by them. Consequently, an effective social influence prediction for each user is critical for a variety of applications such as online recommendation and advertising. Conventional social influence prediction approaches typically design various hand-crafted rules to extract user- and network-specific features. However, their effectiveness heavily relies on the knowledge of domain experts. As a result, it is usually difficult to generalize them into different domains. Inspired by the recent success of deep neural networks in a wide range of computing applications, we design an end-to-end framework, DeepInf, to learn users' latent feature representation for predicting social influence. In general, DeepInf takes a user's local network as the input to a graph neural network for learning her latent social representation. We design strategies to incorporate both network structures and user-specific features into convolutional neural and attention networks. Extensive experiments on Open Academic Graph, Twitter, Weibo, and Digg, representing different types of social and information networks, demonstrate that the proposed end-to-end model, DeepInf, significantly outperforms traditional feature engineering-based approaches, suggesting the effectiveness of representation learning for social applications.Comment: 10 pages, 5 figures, to appear in KDD 2018 proceeding

Censorship Can be Counterproductive: Why Are Certain Kinds of Political Rumors more Credible than Others? An Experiment on Chinese Social Media

HonorsPolitical ScienceUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/169427/1/wuziyi.pd

Implications of social media on end-user personality

Social media are playing an increasing role in today’s living.In Malaysia, the usage of social media has shown a significant growth in the last few years.The importance of studies concerning social media and personality is increasing day by day in line with the popularity of social media use, yet research into social media use in relation to personality traits remains rather limited.The existing literature on social media usage and its implications on end-user personality in Malaysia are also limited.The current research outlined two objectives, which are to identify the profile of social media usage among users in Malaysia, including experience, frequency of use, purpose, and reasons of social media usage, and to examine the effects of social media usage on the five factor personality traits.The study employed a cross-sectional survey using self-administered questionnaire which was distributed among university students who use social media via printed and online questionnaires.The population of this study is students in one of the public universities in Malaysia.The selections of subject being studied have been carried out based on active use of social media in everyday life. Drawing upon the Five-Factor Model of personality traits, a research model that examines the effect of social media on personality traits was developed. Questionnaires for the social media profile are adapted from Pew Internet Report and the Five-Factor Model items were adopted from the International Personality Item Pool.Result shows that majority of the respondents spent below RM150 on telephone and Internet while more than 95% owned notebook computer and almost 79% owned smartphones.The highest score for purpose of using social media is to communicate, either with friends or families.The research model has been validated through survey data collected from 382 social media users, and the analysis results provide evidence to the hypothesized relationships.The current study generates new knowledge on the literature of social media and personality traits; it also sheds lights on the social media profiling among university students. This research extends better theoretical framework to the existing literature through survey regarding the issues related to personality traits and social media

Internet Monitor 2014: Reflections on the Digital World: Platforms, Policy, Privacy, and Public Discourse

This publication is the second annual report of the Internet Monitor project at the Berkman Centerfor Internet & Society at Harvard University. As with the inaugural report, this year’s edition is a collaborative effort of the extended Berkman community. Internet Monitor 2014: Reflections on the Digital World includes nearly three dozen contributions from friends and colleagues around the world that highlight and discuss some of the most compelling events and trends in the digitally networked environment over the past year. The result, intended for a general interest audience, brings together reflection and analysis on a broad range of issues and regions — from an examination of Europe’s “right to be forgotten” to a review of the current state of mobile security to an exploration of a new wave of movements attempting to counter hate speech online — and offers it up for debate and discussion. Our goal remains not to provide a definitive assessment of the “state of the Internet” but rather to provide a rich compendium of commentary on the year’s developments with respect to the online space. Last year’s report examined the dynamics of Internet controls and online activity through the actions of government, corporations, and civil society. We focus this year on the interplay between technological platforms and policy; growing tensions between protecting personal privacy and using big data for social good; the implications of digital communications tools for public discourse and collective action; and current debates around the future of Internet governance. The report reflects the diversity of ideas and input the Internet Monitor project seeks to invite. Some of the contributions are descriptive; others prescriptive. Some contain purely factual observations; others offer personal opinion. In addition to those in traditional essay format, contributions this year include a speculative fiction story exploring what our increasingly data-driven world might bring, a selection of “visual thinking” illustrations that accompany a number of essays, a “Year in Review” timeline that highlights many of the year’s most fascinating Internet-related news stories (and an interactive version of which is available at the netmonitor.org), and a slightly tongue-in-cheek “By the Numbers” section that offers a look at the year’s important digital statistics. We believe that each contribution offers insights, and hope they provoke further reflection, conversation, and debate in both offline and online settings around the globe