Computational Social Science

By Program Website. 2019

435 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In General Social Sciences

Citations in the corpus

Collaborative Filtering beyond the User-Item Matrix (2014, neutral): “The emergence of social networks has impacted a wide range of research disciplines in the past years [Grossman 2006; Lazer et al. 2009; Watts 2007], and recommender systems are no exception.”
Three maps and three misunderstandings: A digital mapping of climate diplomacy (2014, positive): “By this article, we wish to contribute to the debate on digital data in the social sciences (cf. Giles, 2012; Lazer et al., 2009) by proposing an approach that is neither enthusiastic nor alarmist.”
Detection and Resolution of Rumours in Social Media (2017, neutral): “arXiv:1704.00656v3 [cs.CL] 3 Apr 2018 32:2 A. Zubiaga et al. 1 INTRODUCTION Social media platforms are increasingly being used as a tool for gathering information about, for example, societal issues (Lazer et al. 2009 ), and to nd out about the latest developments during breaking news stories (Phuvi”
Critical analysis of Big Data challenges and analytical methods (2017, neutral): “Extant studies surrounding BD challenges have paid attention to the difficulties of understanding the notion of BD (Hargittai, 2015), decision-making of what data are generated and collected (Crawford, 2013), issues of privacy (Lazer et al., 2009) and ethical considerations relevant to mining such d”
Echo Chambers: Emotional Contagion and Group Polarization on Facebook (2016, neutral): “Computational social science 18 seems to be a powerful tool for a better understanding of the cognitive and social dynamics behind misinformation spreading.”
Big Data for Development: A Review of Promises and Challenges (2016, neutral): “Alternatively, there might emerge a privileged set of academic researchers presiding over private data… Neither scenario will serve the long-term public interest” (Lazer et al., 2009).”
Developing Age and Gender Predictive Lexica over Social Media (2014, positive): “Use of social media has enabled the study of psychological and social questions at an unprecedented scale (Lazer et al., 2009).”
Self-Governance Through Group Discussion in Wikipedia (2011, neutral): “As these applications rise in popularity and as more of social life takes place in computer-mediated settings, the need for methods that leverage the rich, socially interactive, and longitudinal nature of these data expand (Lazer et al., 2009; Shniederman, 2008).”