SOCIAL MEDIA INSTRUCTION IN JOURNALISM AND MASS COMMUNICATIONS HIGHER EDUCATION

The purpose of this research is to examine how university-level journalism programs throughout the country are teaching, utilizing, and confronting the new and developing topic of social media. Examined in this research is how journalism programs incorporate social media instruction into their curriculum, how they put it to practice on their program's website, and how and if their tracks or sequences have changed in name and content to reflect an industry shift towards digital, interactive and social media. The questions this thesis will answer are (1) how are journalism schools throughout the country are teaching social media, teaching with social media, and teaching about social media; (2) do social and new media have a place in journalism curricula; and (3) how do changes in the media industry and journalism school curricula coincide

THE ROLE OF ACCOUNT FEATURES AND SOCIAL NETWORKS ON PERCEIVED QUALITY OF INFORMATION SHARERS ON SOCIAL MEDIA

In today’s complex social media environments, users are inundated with news and information. Due to the affordances of the internet, not all content is created equal and much of what exists online is less-than-quality. However, it is important for online users to locate trustworthy and reliable information. It is also important to understand how social media account features and social network connections may mediate users’ evaluations of quality on social media. This dissertation presents a multifaceted look at how users evaluate the quality (i.e. trustworthiness and reliability) of news and information sharers on social media. This work is comprised of three unique, yet complementary studies, that use several methods including survey, social network analysis and statistical analysis. Each study focuses on different types of information sharers—unknown users, network connections, and news organizations. Taken together they suggest that sharers of information are central to users’ propensity to trust and rely on information itself. At a high level, this dissertation suggests the following: (1) when examining unknown information sharers, U.S. audiences are more likely to trust and rely on accounts that are gender-neutral and share a cultural background; (2) there is no relationship between more connected nodes within a person’s social network and trust in news shared by that connection, and young adult Facebook users report having low levels of trust in news shared by friends; and (3) news consumers look for tangible signals of reliability and trustworthiness, like About descriptions and official website links, when assessing news organization social media profiles. This work shows that beyond the reliability of news content, social media users depend on signals, social ties, and platform features to determine trust and reliability in news sharers. Though users consider many factors when assessing credibility of information on social media (e.g. verification status of the sharer, prior interaction with a sharer) the role and influence of the sharer has not been substantially studied in the evaluative process

Analyzing a fake news authorship network

This project synthesizes a set of 246 fake news websites previously identified in three earlier research projects. From this dataset, we extract a set of all authors who have written for these sites in 2016. This authorcentric dataset is itself a contribution that will allow future analysis of the fake news ecosystem. Based on the data we collected, we construct a network of fake news sites, linking them if they shared a common author. Our analysis shows a tight cluster of author-sharing sites, with a small core set of sites sharing dozens of authors

Analyzing topic and stance in fake news stories

The term "fake news" gained traction during the 2016 US presidential election and campaign cycle. Previous work on this data set identified seven themes in fake news articles, including positions opposing or favoring groups or individuals, conspiracy theories and racist messaging. This work analyzed hundreds of those fake news articles (N=272) in order to better understand the topics covered and stances taken. Seven main topics were identified in the articles. The majority of articles took a stance against an individual, group or topic. Among the articles that took a stance, the majority of them were pro-Trump

Analyzing topic and stance in fake news stories

The term "fake news" gained traction during the 2016 US presidential election and campaign cycle. Previous work on this data set identified seven themes in fake news articles, including positions opposing or favoring groups or individuals, conspiracy theories and racist messaging. This work analyzed hundreds of those fake news articles (N=272) in order to better understand the topics covered and stances taken. Seven main topics were identified in the articles. The majority of articles took a stance against an individual, group or topic. Among the articles that took a stance, the majority of them were pro-Trump