Effects of Personality Traits on Usage of Social Networking Service

Author(s):  
Shiro Uesugi
2021 ◽  
pp. 146144482110245
Author(s):  
Greta Jasser ◽  
Jordan McSwiney ◽  
Ed Pertwee ◽  
Savvas Zannettou

With large social media platforms coming under increasing pressure to deplatform far-right users, the Alternative Technology movement (Alt-Tech) emerged as a new digital support infrastructure for the far right. We conduct a qualitative analysis of the prominent Alt-Tech platform Gab, a social networking service primarily modelled on Twitter, to assess the far-right virtual community on the platform. We find Gab’s technological affordances – including its lack of content moderation, culture of anonymity, microblogging architecture and funding model – have fostered an ideologically eclectic far-right community united by fears of persecution at the hands of ‘Big Tech’. We argue that this points to the emergence of a novel techno-social victimology as an axis of far-right virtual community, wherein shared experiences or fears of being deplatformed facilitate a coalescing of assorted far-right tendencies online.


Author(s):  
Serhii Puhach

The intensive development of new information and communication technologies (ICT) has led to major changes in society. The widespread use of smartphones and mobile communications has allowed today to create new programs and services to improve human life. This development changes the established habits of human communication, the relationship between society and the environment. A social networking service (SNS) is a service (on a website or through a mobile application) that allows users to share a personal profile and establish contacts with other users. Social networking services affect the territorial organization of society and can be used for the development of both settlements and entire territories to make their development more sustainable and balanced. The study of social networking services is currently on the rise. The joint efforts of many sciences (sociology, psychology, geography, mathematics, statistics, computer science, etc.) are needed to understand the subject essence of the phenomenon and to analyze data. Approaches to the study of social networking services can be divided into three large groups: 1) in terms of human relations and relationships; 2) in terms of content distributed on the network; 3) in terms of spatial aspects of the functioning of the social network. In Ukraine, there are no detailed studies of the spatial aspects of the spread of social networking services at the local level. In the Ternopil region, there is a pattern of concentration of the majority of Facebook and Instagram users in the largest cities, namely Ternopil, Chortkiv, Berezhany, Kremenets. Buchach, Borshchiv, Zalishchyky, Terebovlya, and Shumsk districts stand out among the districts by the number of users. An important indicator that characterizes the spread of social networking services is the penetration rate of the social network, which is calculated as the ratio of the number of users in a certain territory to the population living in it. Cities of regional subordination differ in terms of the penetration rate of SNS. The highest values were observed in Chortkiv, Ternopil, Kremenets cities. The penetration rate of social networking services in the administrative districts of Ternopil region is much lower. A relatively high rate (over 30%) was recorded in Buchach, Berezhany and Shumsk districts. Extremely low penetration rate (less than 5%) is in Zbarazh, Chortkiv, Zboriv districts which are adjacent to the cities of regional subordination. The social networking service Instagram is inferior to Facebook in level of development, and its main users are mainly young people. However, in the territories where the rate of Facebook penetration is the lowest in the region (Ternopil, Zbarazh, Chortkiv, Zboriv districts), the predominance of Instagram is noted. Thus, the main patterns of spatial distribution of SNS’ Facebook and Instagram in Ternopil region are: concentration of users in the largest cities, especially in the regional center Ternopil City (half of Facebook and Instagram users in the region); the number of users is proportional to the population in the territorial unit; small number of users and low penetration rate of the SNS’ in the administrative districts adjacent to the cities of regional subordination Ternopil and Chortkiv; among administrative districts, higher indicators of social network development are typical for northern and southern districts in comparison with central ones. Key words: social networking service (SNS), penetration rate of the SNS, Facebook, Instagram, Ternopil region.


Author(s):  
Hamed Qahri-Saremi ◽  
Isaac Vaghefi ◽  
Ofir Turel

Prior studies have primarily used "variable-centered" perspectives to identify factors underlying user responses to social networking site (SNS) addiction, their predictors and outcomes. This paper extends this perspective by taking a person-centered approach to examine (1) the prototypical subpopulations (profiles) of users' extent of SNS addiction and responses to it, (2) how affiliations with these profiles can explain user behaviors toward SNS use, and (3) how personality traits can predict affiliations with these profiles. To this end, we propose a typological theory of SNS addiction and user responses to it via two empirical, personcentered studies. Study 1 draws on survey data from 188 SNS users to develop a typology of users based on the extent of their SNS addiction and their responses to it. It further examines the relations between affiliation with these profiles and users' SNS discontinuance intention, as a typical behavioral response to SNS addiction. Study 2 uses survey data from 284 SNS users to validate the user typology developed in Study 1 and investigate its relations to users' Big Five personality traits. Our findings shed light on a typology of five prototypical profiles of SNS users-cautious, regular, consonant, dissonant, and hooked-who differ in their extent of SNS addiction and their cognitive, emotional, and behavioral responses to it. Our findings also demonstrate how Big Five personality traits can predict user affiliations with these prototypical profiles.


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