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In the age of social media, when publishers are vying for consumer attention, click-baits have become very common. Not only viral websites but also mainstream publishers, such as news channels, use click-baits for generating traffic. Therefore, click-bait detection and prediction of click-bait virality have become important challenges for social media platforms to keep the platform click-bait free and give a better user experience. The purpose of this study is to try exploring how the contents of the social media posts and the article can be used to explain and predict social media posts and the virality of a click-bait.

This study has used 17,745 tweets from Twitter with 4,370 click-baits from top 27 publishers and applied econometric along with machine learning methods to explain and predict click-baitiness and click-bait virality.

This study finds that language formality, readability, sentiment scores and proper noun usage of social media posts and various parts of the target article plays differential and important roles in click-baitiness and click-bait virality.

The paper contributes toward the literature of dark behavior in social media at large and click-bait prediction and explanation in particular. It focuses on the differential roles of the social media post, the article shared and the source in explaining click-baitiness and click-bait virality via psycho-linguistic framework. The paper also provides explanability to the econometric and machine learning predictive models, thus performing methodological contribution too.

The paper helps social media managers create a mechanism to detect click-baits and also predict which ones of them can become viral so that corrective measures can be taken.

To the best of the authors’ knowledge, this is one of the first papers which focus on both explaining and predicting click-baitiness and click-bait virality.

The purpose of this study is to unpack the antecedents and consequences of clickbait prevalence in online media at two different levels, namely, (1) Headline-level: what characteristics of clickbait headlines attract user clicks and (2) Publisher-level: what happens to publishers who create clickbait on a prolonged basis.

To test the proposed conjectures, the authors collected longitudinal data in collaboration with a leading company that operates more than 500 WeChat official accounts in China. This study proposed a text mining framework to extract and quantify clickbait rhetorical features (i.e. hyperbole, insinuation, puzzle, and visual rhetoric). Econometric analysis was employed for empirical validation.

The findings revealed that (1) hyperbole, insinuation, and visual rhetoric entice users to click the baited headlines, (2) there is an inverted U-shaped relationship between the number of clickbait headlines posted by a publisher and its visit traffic, and (3) this non-linear relationship is moderated by the publisher's age.

This research contributes to current literature on clickbait detection and clickbait consequences. Future studies can design more sophisticated methods for extracting rhetorical characteristics and implement in different languages.

The findings could aid online media publishers to design attractive headlines and develop clickbait strategies to avoid user churn, and help managers enact appropriate regulations and policies to control clickbait prevalence.

The authors propose a novel text mining framework to quantify rhetoric embedded in clickbait. This study empirically investigates antecedents and consequences of clickbait prevalence through an exploratory study of WeChat in China.

This paper aims to propose an Immersive Virtual Reality program to teach Information Literacy skills to college students. The proposal aims to expand the horizon of instruction into cyberspace.

The paper explains the planning, cost and logistics required to implement such a program. The virtual reality (VR) program puts students in everyday situations that require “common sense” decision-making actions, then transfers them into a library setting requiring them to use the exact same reasoning. A crucial component of Information Literacy is Digital Literacy, so this program includes scenarios that require students to identify “Fake News.”

The paper provides insights about the Game Design Document, Concept and Design Phases as well as Performance Specifications, Deliverables and for Return on Investments used for formative assessments.

Without securing sponsorships or collaborations due to the inordinate expense of creating virtual worlds this program remains unfunded.

The program is a revolutionary approach to Information Literacy instruction. It shows students that they inherently possess the cognitive tools necessary for critical evaluation skills needed to be Information Literate.

VR can transmit knowledge without students feeling they are being preached at.

This program fulfills an identified need to keep libraries relevant in this technologically advanced Digital Age. This radical VR program represents a truly transformational approach to instruction that can catapult us into the virtual and eventual future of Libraries.