User Analytics in Online Social Networks: Evolving from Social Instances to Social Individuals

Abstract

In our era of big data and information overload, content consumers utilise a variety of sources to meet their data and informational needs for the purpose of acquiring an in-depth perspective on a subject, as each source is focused on specific aspects. The same principle applies to the online social networks (OSNs), as usually, the end-users maintain accounts in multiple OSNs so as to acquire a complete social networking experience, since each OSN has a different philosophy in terms of its services, content, and interaction. Contrary to the current literature, we examine the users’ behavioural and disseminated content patterns under the assumption that accounts maintained by users in multiple OSNs are not regarded as distinct accounts, but rather as the same individual with multiple social instances. Our social analysis, enriched with information about the users’ social influences, revealed behavioural patterns depending on the examined OSN, its social entities, and the users’ exerted influence. Finally, we ranked the examined OSNs based on three types of social characteristics, revealing correlations between the users’ behavioural and content patterns, social influences, social entities, and the OSNs themselves.

From Questionable Incident to Political Scandal

“…Following the research goal to analyze how journalists on social media posted during the Ibiza affair, tweets from influential political journalists with active Twitter accounts were collected. The influence of the journalists was measured according to Razis et al (2022), who incorporated the most recent activities of a Twitter account and a followers- to-following ratio in their metric. The sampling process is based on prior methodological considerations, focusing on "case selection strategically in alignment with the inquiry's purpose, primary questions, and data being collected" (Patton, 2022(Patton, , p. 1173.…”