Hai Liang

How people react to Zika virus outbreaks on Twitter? A computational content analysis

Zika-related Twitter incidence peaked after the World Health Organization declared an emergency. Five themes were identified from Zika-related Twitter content: (1) societal impact of the outbreak; (2) government, public and private sector, and general public responses to the outbreak; (3) pregnancy and microcephaly: negative health consequences related to pregnant women and babies; (4) transmission routes; and (5) case reports. User-generated contents sites were preferred direct information channels rather than those of the government authorities.

Testing Propositions Derived from Twitter Studies: Generalization and Replication in Computational Social Science

Replication is an essential requirement for scientific discovery. The current study aims to generalize and replicate 10 propositions made in previous Twitter studies using a representative dataset. Our findings suggest 6 out of 10 propositions could not be replicated due to the variations of data collection, analytic strategies employed, and inconsistent measurements. The study’s contributions are twofold: First, it systematically summarized and assessed some important claims in the field, which can inform future studies. Second, it proposed a feasible approach to generating a random sample of Twitter users and its associated ego networks, which might serve as a solution for answering social-scientific questions at the individual level without accessing the complete data archive.

Privacy protection and self-disclosure across societies: A study of global Twitter users

Privacy is a culturally specific phenomenon. As social media platforms are going global, questions concerning privacy practices in a cross-cultural context become increasingly important. The purpose of this study is to examine cultural variations of privacy settings and self-disclosure of geolocation on Twitter. We randomly selected 3.3 million Twitter accounts from more than 100 societies. Results revealed considerable cultural and societal differences. Privacy setting in collectivistic societies was more effective in encouraging self-disclosure; whereas it appeared to be less important for users in individualistic societies. Internet penetration was also a significant factor in predicting both the adoption of privacy setting and geolocation self-disclosure. However, we did not find any direct relationships between cultural values and self-disclosure.

Network Redundancy and Information Diffusion: The Impacts of Information Redundancy, Similarity, and Tie Strength

It remains controversial whether community structures in social networks are beneficial or not for information diffusion. This study examined the relationships among four core concepts in social network analysis—network redundancy, information redundancy, ego-alter similarity, and tie strength—and their impacts on information diffusion. By using more than 6,500 representative ego networks containing nearly 1 million following relationships from Twitter, the current study found that (1) network redundancy is positively associated with the probability of being retweeted even when competing variables are controlled for; (2) network redundancy is positively associated with information redundancy, which in turn decreases the probability of being retweeted; and (3) the inclusion of both ego-alter similarity and tie strength can attenuate the impact of network redundancy on the probability of being retweeted.

Do Chinese Internet users care about news? Tracking news consumers on the Internet in a metropolis 2009–2011

This study aims to explore the patterns and trends of Internet news use in a Chinese metropolis, Shanghai. By analyzing news webpage browsing data from three selected months in 2009, 2010, and 2011, we seek to present some evidence other than self-report data, which were widely used in past research but subject to the influence of memory limitation and social desirability. Our findings are: First, Internet users in Shanghai paid more attention to soft news, and finance and economy news, than to social and political news both in terms of visit times and visit duration. Second, news page visits and the amount of time people spent on reading news online suggest clear monotonic growth across all categories of news content over a three-year period. Third, despite the growing amount of visits and time used for online news, the proportion of visits and time devoted to news viewing to total webpage visits and time spent online decreased significantly. However, “social and political news” and “finance and economy news” did not experience any decline. Finally, existing gaps were identified between different demographic groups in terms of news reading frequency online, but no clear trends were identified concerning how the gaps developed over time.