This recorded talk with Susan Benesch, a fellow at Harvard’s Berkman Center for Internet & Society deals with data driven methods to decrease hate online.
This explanatory thesis is concerned with user generated text, audio and video media. According to Tsagkias two aspects, the social and user generated content, led to the development of two main research branches in social media analysis.
This article concerns whether social media is a valid indicator of political behavior. As the authors discuss, there is considerable debate about the validity of data extracted from social media for studying offline behavior.
This paper sets out to interpolate and predict state-level polling at the daily level by employing a dataset of over 500GB of political tweets from the final months of the 2012 presidential campaign.
This 2013 article analyzes content generated on Twitter during the attacks at the Boston Marathon in April 2013. The authors perform an in-depth characterization of what factors influenced malicious content and profiles becoming viral.
The authors of this 2011 article hypothesize that the results of Google Trends, given its daily and weekly reports on queries related to various industries may be correlated to the current level of economic activity in these industries.
This survey reviews the literature and concepts of the data mining of social networks, with special emphasis on their representation as a graph structure. The article is divided into two principal parts:
This article focuses on Data Mining and Social Network Analysis (SNA) amongst bloggers, and in particular the mining of racist groups and cyber hate communities in online blogging websites.
This portal gathers an annotated collection of recent research on the ways in which social media and new technologies may be leveraged in the fight against violent extremism