We examine how word-of-mouth learning may lead to uniform and possibly inefficient actions in finite time among a network of agents. In our model, agents are identically informed a priori and observe network neighbors’ actions as well as the payoffs of some or all of those actions (a...

This paper develops strategic foundations for an important statistical model of random networks with heterogeneous expected degrees. Based on this, we show how social networking services that subtly alter the costs and indirect benefits of relationships can cause large changes in behavior and...

The development of stochastic models for the analysis of social networks is an important growth area in contemporary statistics. The last few decades have witnessed the rapid development of a variety of statistical models capable of representing the global structure of an observed network in...

Social media have great potential to support diverse information sharing, but there is widespread concern that platforms like Twitter do not result in communication between those who hold contradictory viewpoints. Because users can choose whom to follow, prior research suggests that social media...

As a key task of fine-grained sentiment analysis, aspect-based sentiment analysis aims to analyse people's opinions at the aspect level from user-generated texts. Various sub-tasks have been defined according to different scenarios, extracting aspect terms, opinion terms, and the corresponding...

This paper uses the popular social networking site Twitter to test recent theories on the importance of communication through networks. I create a unique data set that precisely measures the network size and credibility of each contributor to the site. I test the theory of DeMarzo et al (2003)...

The user has become central to the way technology is conceptualized, designed, and studied in sociotechnical research and human-computer interaction; recently, non-users have also become productive foci of scholarly analysis. This paper argues that a focus on individualized users and non-users...