Benjamin D. Horne

Identifying the Social Signals That Drive Online Discussions: A Case Study of Reddit Communities

Increasingly people form opinions based on information they consume on online social media. As a result, it is crucial to understand what type of content attracts peoples attention on social media and drive discussions. In this paper we focus on online discussions. Can we predict which comments and what content gets the highest attention in an online discussion? How does this content differ from community to community? To accomplish this, we undertake a unique study of Reddit involving a large sample comments from 11 popular subreddits with different properties. We introduce a large number of sentiment, relevance, content analysis features including some novel features customized to reddit. Through a comparative analysis of the chosen subreddits, we show that our models are correctly able to retrieve top replies under a post with great precision. In addition, we explain our findings with a detailed analysis of what distinguishes high scoring posts in different communities that differ along the dimensions of the specificity of topic and style, audience and level of moderation.

Impact of message sorting on access to novel information in networks

In social networks, individuals and systems work side by side. While individuals make decisions to filter or forward information, systems also prioritize and sort information to manage and assist individual information processing. It has long been argued that system level manipulations can reduce access of individuals to novel information. In this paper, we study how sorting of messages in ones inbox can help or hinder access of diverse information in the network through simulation of cognitively bounded actors. We show that first-in-first-out (FIFO) method of message sorting is ideal in bursty information arrival rates and in networks with lower diameter. Last-in-first-out (LIFO) method of message sorting is ideal for streaming information arrival, but leads to information overload in bursty scenarios by creating too many redundant copies of some of the information in the network. In short, the ideal message sorting method that enhances access to diverse information depends on the network type and information access patterns.

Assessing the News Landscape: A Multi-Module Toolkit for Evaluating the Credibility of News

Today, journalist, information analyst, and everyday news consumers are tasked with discerning and fact-checking the news. This task has became complex due to the ever-growing number of news sources and the mixed tactics of maliciously false sources. To mitigate these problems, we introduce the The News Landscape (NELA) Toolkit: an open source toolkit for the systematic exploration of the news landscape. NELA allows users to explore the credibility of news articles using well-studied content-based markers of reliability and bias, as well as, filter and sort through article predictions based on the users own needs. In addition, NELA allows users to visualize the media landscape at different time slices using a variety of features computed at the source level. NELA is built with a modular, pipeline design, to allow researchers to add new tools to the toolkit with ease. Our demo is an early transition of automated news credibility research to assist human fact-checking efforts and increase the understanding of the news ecosystem as a whole.

Effects of Priming on Online Discussion Behavior

Online disinhibition effect describes the phenomenon where people feel less restrained in an online environment. People are therefore more likely to express thoughts and opinions that they normally would not share in a face-to-face interaction (Suler, 2004). Online disinhibition effect could either be benign or toxic. Students and instructors in an online learning environment often experience toxic disinhibition in several forms, including arguments about grades, emotional outbursts, potential death threat to the instructor, personal attacks, swearing, and heated arguments using upper-case letters (Rose, 2014). Suler (2004) proposed six factors that contribute to the online disinhibition effect. These six factors include dissociative anonymity, invisibility, asynchronicity, solipsistic introjection, dissociative imagination, and minimization of authority. Not all six factors proposed by Suler (2004) have received equal empirical evidence. Also, not all factors are relevant to online learning environments. This study therefore focused on the factor of invisibility and the lack of contextual cues as a result of invisibility. One of the ways to provide contextual cues in a situation that lacks face-to-face interaction is through the usage of color signaling. Color signaling refers to the usage of colored text to convey information (Elliot, 2015; Lemarié, Lorch, Eyrolle & Virbel, 2008). This study looked at the effects of red color signaling, because the color red has been associated with dominance and aggression (Elliot, Maier, Moller, Friedman & Meinhardt, 2007). It is also often associated with some type of warning sign, such as a stop light or a stop sign (Elliot, 2015). The implicit warning and danger conveyed by the color red has been shown to result in inhibited performance, such that participants who were exposed to the color red had lower performance on the subsequent achievement task (Elliot, Maier, Reidman & Meinhardt, 2007; Gnambs, Appel & Batinic, 2010). Similar effects have also been demonstrated in online gaming situations, where red priming messages lowered the amount of negative language usage (Maher, 2016). It is therefore likely that red priming message could also lower any potential toxic disinhibition in an online learning environment. The current study included two experiments that tested the effects of red priming message and black priming message on 1) participants’ expressed sentiment in their open- ended discussion posts, 2) participants’ self-rating of verbal aggressiveness, and 3) the total number of words generated in the open-ended responses. Past studies have shown that red color could inhibit task performance and reduce offensive language, but it is not clear how a red color priming message might affect discussion posts in a simulated online classroom. Similarly, black color has been shown not to inhibit behavior, but it is not clear how a priming message such as “exercise courtesy and professionalism” might affect participants’ behavior in an online discussion post. Results from the study indicated that red priming message caused participants to rate themselves as less verbally aggressive. This was likely due to increased attention to the priming message and the implicit warning conveyed by the color red. There was evidence that red priming message lowered the amount of negative sentiment expressed in the discussion posts. The results approached statistical significance, but it was not significant probably due to the low levels of negative sentiment expressed. Black priming message was found to be ineffective in lowering verbal aggression rating or negative sentiment expression. The findings from the current study have practical implications in the design of online courses. Instructors could use red priming messages as a strategy to promote a less verbally aggressive and negative online discussion environment.