Understanding the link between audience engagement metrics and the perceived quality of online news using machine learning

This article aims to explain the perceived quality of online news articles. Discovering which elements of a news story influence readers' perceptions could drive online popularity, which is the paramount factor of digital news readership. This work explores an approach to use tree-based machine learning algorithms to address this problem based on selected characteristics, which measure engagement, drawn from prior research mostly developed by communication scientists. A proposed extended model is used to examine the association between the engagement features and perceived quality concerning all the articles depending mainly on their genre. To demonstrate the capacity of using predictive analytics to facilitate journalistic news writing the proposed methodology is applied on a novel data set with 200K articles in total constructed from a blog site. The results of phase A, indicate interesting correlations between the features and the perceived quality of the articles. In stage B, the paper seeks to extract a set of rules that can be used as guidelines for authors in the writing of their next articles, indicating the probability of popularity that their articles may gain if these rules are taken into consideration

What Influences Content Popularity? An Empirical Investigation of Voting in Social Q&A Communities

Users in content communities are now empowered by the voting mechanism to determine the popularity of content. However, it is criticized that the social network of the author may bias the voting outcome. On the basis of dual-process theory and literature on the influence of social relationship, this study examines how the attributes of the content and the social relationships of the author jointly influence the popularity of the answer in a social Q&A community. Results reveal that the number of pictures in the answer increases its popularity, while the effect of the number of words is non-linear. As the answer gets longer, the number of votes initially decreases and then increases. Followers can increase answer popularity, whereas friends cannot. Moreover, the influence of content decreases for authors with numerous followers, while the influence of content increases for authors with many friends

Scientific Knowledge Communication in Online Q&A Communities: Linguistic Devices as a Tool to Increase the Popularity and Perceived Professionalism of Knowledge Contribution

With the popularity of question-and-answer (Q&A) communities, widespread dissemination of scientific knowledge has become more viable than ever before. However, those contributing high-quality professional scientific knowledge are confronted with the challenge of making their contributions popular, since non expert readers may not recognize the importance of their contributions given the massive amount of information available online. In this study, we show that non expert readers are capable of evaluating the professionalism of content contributed in such communities as well as experts. However, we discovered that a salient discrepancy exists between the content non experts favor and the content they perceive as professional. In line with studies that have suggested that writing techniques play an important role in how expert content is received by lay persons, we investigated how the use of linguistic devices affects both the perceived professionalism and the popularity of contributions in Q&A communities. Based on both secondary data and a scenario-based survey, we identified specific linguistic devices that can increase content popularity without reducing perceived professionalism. Additionally, we revealed linguistic devices that increase popularity at the expense of perceived professionalism in this context. Finally, we conducted a laboratory experiment to more firmly establish the causal effects of the linguistic device use. The triangulated findings have important implications for both research and practice on communicating scientific knowledge in Q&A communitie