Online News Sharing

News sharing across different social media platforms is increasingly impacting on our news habits. However, we know very little about what makes news popular in these settings. The current paper details what types of news stories are are shared the most on two social media platforms – Facebook and Twitter. By conducting a qualitative content analysis and comparing data from four Norwegian media outlets we find that editorial comment pieces about 'softer' news topics are more frequently shared than 'harder' news topics from all media outlets-except for TV2. For this latter broadcaster, the results suggest that sensational news and news regarding celebrities allows for viral effects to take place.

In the present study we focus on the use of social network sites by Romanian and German youth in a comparative manner. Our research questions are 1. Are there differences in the use of social network sites by young people in Germany and Romania? 2. Are there differences in the motivation to use social network sites? and 3. How do they see the information shared on social networks? The present study is of exploratory nature and it was only the first step in analyzing the differences between Romanian and German students with respect to the use of SNS such as Facebook, Instagram, Snapchat and WhatsApp. Based on a qualitative methodology, our results cannot be subject for generalization. Nevertheless , we emphasized some relevant tendency such as: a migration towards

Online news users interact with news on digital platforms in different ways. Some take advantage of the technical affordances that allow sharing, liking and commenting, while others do not. Based on a national survey of the Australian adult online news users, this study explores online news users’ different modes of interaction on digital platforms: non-interaction, signalling interaction, and expressive interaction. This study demonstrates that different types of online news users are largely determined by a combination of structural influences and individual factors related to the uptake, reception, and dissemination of news. This study contributes to the growing body of literature on news engagement by exploring the concept of interaction as a more specific term to describe online news behaviours, and identifies different types of news users connected to, rather than disembodied from, their practice. In doing so, this article advances the understanding of news consumption behaviour and its implications for engaging news audiences in the digital age.

In this article we describe a method to estimate the determinants of news sharing in social media. We model news sharing as a function of three behavioral parameters that describe the (i) ideological (cog-nitive) congruence between the users and the news published by a media organization; the (ii) reputation of the media organization; and the (iii) user's attention to issues. The statistical model takes observational social network data as input and extracts all three parameters of interest. Extensions of the proposed model evaluate the users demand for content as well as the level of congruence between users and their preferred media offerings. We exemplify the substantive contributions of the method with data from #Bolsonaro in Brazil, #Maldonado in Argentina, and the #TravelBan in the US. Social Media | News Sharing | Gatekeeping Why do readers share links to news articles in social media feeds? How important are ideological considerations, the reputation of a news organizations, and the attention of users to an issue? In this article, we describe a statistical model that takes as input a matrix of social media embeds and delivers estimates of the importance of ideological (cognitive) congruence , media reputation, and issue attention in news sharing. The proposed model allows researchers to (i) understand news consumption in different regions of a social network; (ii) decompose the demand for content revealed by users; and (iii) estimate the optimal editorial line if news organizations were solely interested in maximizing readership. All three contributions are theoretically informed and of substantive interest to students of the relationship between news consumption and social media. Our research contributes to the growing field of news sharing in social media (Thurman et al., 2019; García-Perdomo et al., 2018; Arendt et al., 2016; Kümpel et al., 2015; Bright, 2016; Boczkowski et al., 2018), providing a valuable tool to derive sharing behavior from aggregate level data. The literature on news sharing is broad, considering subjective, social, rational, and emotional factors that explain sharing behavior. As described by Kümpel (2019) and Boehmer and Tandoc Jr (2015), individual's sharing behavior can be explained by factors such as the trustworthiness of the source (Suh et al., 2010; Wang et al., 2012), the content of the message (Macskassy and Michelson, 2011), the attention to issues (Boyd et al., 2010; Rudat et al., 2014), and the linkages between users and their peer groups. Empirical testing of these models, however, requires a statistical model to extract informative parameters from observational data. Results of our study also inform recent debates on gatekeeping behavior, modeling congruence between the media organization and users as content is activated in different regions of a social media network (Shoemaker and Reese, 2013; Bennett et al., 2008; Aruguete and Calvo, 2018). The proposed strategy allows researchers to use observational social media data to extract theoretically informed parameters of interest. We test the proposed model using news embeds in Twitter and compare three different events in the United States (#TravelBan), Brazil (#Bolsonaro), and Argentina (#Maldonado). The data includes 2,031,518 retweets from 241,271 high activity accounts of the #Trav-elBan; 2,943,993 retweets published by 162,107 high activity accounts from the #Bolsonaro election in Brazil; and 5,325,240 million retweets from 196,066 high activity accounts from the #Maldonado crisis in Argentina.

Social media news sharing has become a central subject of scholarly research in communication studies. To test current theories, it is of an utmost importance to estimate the meaningful parameters of news sharing behavior from observational data. In this article, we retrieve measures of ideological congruence, issue salience, and media reputation to explain news sharing in social media. We describe how the proposed statistical model connects to different strands of the news sharing literature. We then exemplify the usefulness of the model with an analysis of the relationship between ideological congruence and issue salience. Results show that if ideology and salience correlate with each other, the preferences of ideologues (i.e., users who give higher weight to ideological congruence) will be overrepresented in observational data. This will result in the heightened perceptions of polarization. We test the performance of the model using data from Brazil, Argentina, and the United States.