scholarly journals Transforming the 2019-2020 Protest Agenda on Social Network Sites

2021 ◽  
Vol 12 (1 (33)) ◽  
pp. 3-19
Author(s):  
Alexey Belyakov ◽  
Alexander Sokolov ◽  
Svetlana Mironova ◽  
Alexander Frolov ◽  
Elena Isaeva
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Political Communication ◽  
Quantitative Data ◽  
Social Network Sites ◽  
Virtual Space ◽  
Modern World ◽  
Strong Position ◽  
The Impact ◽  
Protest Activity

Social network sites have taken a strong position in the space of socio-political communication. In the modern world, the necessity to analyze events occurring in the virtual space for a relevant reaction to events occurring in reality, is generally recognized. The study of online processes is largely based on the analysis of quantitative data that allows talking about the activity of users and their involvement. However, the meaning of the information transmitted in social networks remains important. In the framework of this study, an attempt is made to determine the specifics of broadcasting protest agendas in social networks and the impact of their transformation on the process of involving users in online protest activity. Examples of 7 protest campaigns accompanied by active coverage in social networks are given. Conclusions are drawn about the specifics of broadcasting protest agendas in social networks and supporting users from their transformation.

scholarly journals IMPACT OF OFFLINE AND ONLINE SOCIAL NETWORKS ON LONELINESS AND MENTAL HEALTH AMONG ITALIAN OLDER PEOPLE

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S529-S529
Author(s):  
Daniele Zaccaria ◽  
Georgia Casanova ◽  
Antonio Guaita
Keyword(s):  
Mental Health ◽  
Social Networks ◽  
Social Network ◽  
Older People ◽  
Online Social Networks ◽  
Social Network Sites ◽  
Well Being ◽  
Controlled Study ◽  
Face To Face ◽  
Causal Impact

Abstract In the last decades the study of older people and social networks has been at the core of gerontology research. The literature underlines the positive health effects of traditional and online social connections and also the social networks’s positive impact on cognitive performance, mental health and quality of life. Aging in a Networked Society is a randomized controlled study aimed at investigating causal impact of traditional face-to-face social networks and online social networks (e.g. Social Network Sites) on older people’ health, cognitive functions and well-being. A social experiment, based on a pre-existing longitudinal study (InveCe - Brain Aging in Abbiategrasso) has involved 180 older people born from 1935 to 1939 living in Abbiategrasso, a municipality near Milan. We analyse effects on health and well-being of smartphones and Facebook use (compared to engagement in a more traditional face-to-face activity), exploiting the research potential of past waves of InveCe study, which collected information concerning physical, cognitive and mental health using international validate scale, blood samples, genetic markers and information on social networks and socio-demographic characteristics of all participants. Results of statistical analysis show that poor social relations and high level of perceived loneliness (measured by Lubben Scale and UCLA Loneliness scale) affect negatively physical and mental outcomes. We also found that gender and marital status mediate the relationship between loneliness and mental wellbeing, while education has not significant effect. Moreover, trial results underline the causal impact of ICT use (smartphones, internet, social network sites) on self-perceived loneliness and cognitive and physical health.

scholarly journals I Know Where You Are Coming From: On the Impact of Social Media Sources on AI Model Performance (Student Abstract)

2020 ◽  
Vol 34 (10) ◽  
pp. 13971-13972
Author(s):  
Yang Qi ◽  
Farseev Aleksandr ◽  
Filchenkov Andrey
Keyword(s):  
Machine Learning ◽  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Model Performance ◽  
User Profiling ◽  
Personalized Recommendation ◽  
Modal Data ◽  
Social Media Networks ◽  
The Impact

Nowadays, social networks play a crucial role in human everyday life and no longer purely associated with spare time spending. In fact, instant communication with friends and colleagues has become an essential component of our daily interaction giving a raise of multiple new social network types emergence. By participating in such networks, individuals generate a multitude of data points that describe their activities from different perspectives and, for example, can be further used for applications such as personalized recommendation or user profiling. However, the impact of the different social media networks on machine learning model performance has not been studied comprehensively yet. Particularly, the literature on modeling multi-modal data from multiple social networks is relatively sparse, which had inspired us to take a deeper dive into the topic in this preliminary study. Specifically, in this work, we will study the performance of different machine learning models when being learned on multi-modal data from different social networks. Our initial experimental results reveal that social network choice impacts the performance and the proper selection of data source is crucial.

scholarly journals Personality and the Impact of Celebrity Endorsements on Instagram

2021 ◽  
Vol 18 (3) ◽  
pp. 468-474
Author(s):  
Yair Amichai-Hamburger ◽  
Shir Etgar ◽  
Hadar Gil-Ad ◽  
Michal Levitan-Giat ◽  
Gaya Raz
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Locus Of Control ◽  
Strong Influence ◽  
Online Social Network ◽  
Strong Impact ◽  
Celebrity Endorsements ◽  
Internal Locus Of Control ◽  
The Impact ◽  
The Relationship

Celebrities are famous people who often belong to entertainment industry. They are known to have a strong influence on people’s behavior. In the digital age this impact has expanded to include the online arena. Celebrities increasingly utilize Instagram, an online social network, to promote commercial products. It is important to learn to what extent people are influenced by this type of promotion and what sort of people are likely to be swayed by it. Research has demonstrated that people’s personalities have a strong impact on their behaviors online. However, until now, these investigations have not included the relationship between personality and the degree of celebrity influence through social networks. This study examines how much the personality of a user is related to the degree to which he or she is influenced by these Celebrity Instagram messages. Participants comprised 121 students (34 males, 87 females). They answered questionnaires which focused on their personality and were asked about the degree of influence celebrities exerted upon them through Instagram. Results showed that people who are characterized as being open and having an internal locus of control are more resistant to such celebrity influences. This paper demonstrates that the personality of a recipient is likely to influence the degree of impact that a celebrity endorsement is likely to produce. The implications of these results are discussed.

scholarly journals Retweet Prediction Based on User Behavior

2021 ◽  
Author(s):  
Syeda Nadia Firdaus
Keyword(s):  
Machine Learning ◽  
Social Networks ◽  
Social Network ◽  
Prediction Model ◽  
Matrix Factorization ◽  
Information Diffusion ◽  
User Behavior ◽  
Past Research ◽  
The Difference ◽  
The Impact

Social network is a hot topic of interest for researchers in the field of computer science in recent years. These social networks such as Facebook, Twitter, Instagram play an important role in information diffusion. Social network data are created by its users. Users’ online activities and behavior have been studied in various past research efforts in order to get a better understanding on how information is diffused on social networks. In this study, we focus on Twitter and we explore the impact of user behavior on their retweet activity. To represent a user’s behavior for predicting their retweet decision, we introduce 10-dimentional emotion and 35-dimensional personality related features. We consider the difference of a user being an author and a retweeter in terms of their behaviors, and propose a machine learning based retweet prediction model considering this difference. We also propose two approaches for matrix factorization retweet prediction model which learns the latent relation between users and tweets to predict the user’s retweet decision. In the experiment, we have tested our proposed models. We find that models based on user behavior related features provide good improvement (3% - 6% in terms of F1- score) over baseline models. By only considering user’s behavior as a retweeter, the data processing time is reduced while the prediction accuracy is comparable to the case when both retweeting and posting behaviors are considered. In the proposed matrix factorization models, we include tweet features into the basic factorization model through newly defined regularization terms and improve the performance by 3% - 4% in terms of F1-score. Finally, we compare the performance of machine learning and matrix factorization models for retweet prediction and find that none of the models is superior to the other in all occasions. Therefore, different models should be used depending on how prediction results will be used. Machine learning model is preferable when a model’s performance quality is important such as for tweet re-ranking and tweet recommendation. Matrix factorization is a preferred option when model’s positive retweet prediction capability is more important such as for marketing campaign and finding potential retweeters.

scholarly journals Retweet Prediction Based on User Behavior

2021 ◽  
Author(s):  
Syeda Nadia Firdaus
Keyword(s):  
Machine Learning ◽  
Social Networks ◽  
Social Network ◽  
Prediction Model ◽  
Matrix Factorization ◽  
Information Diffusion ◽  
User Behavior ◽  
Past Research ◽  
The Difference ◽  
The Impact

Social network is a hot topic of interest for researchers in the field of computer science in recent years. These social networks such as Facebook, Twitter, Instagram play an important role in information diffusion. Social network data are created by its users. Users’ online activities and behavior have been studied in various past research efforts in order to get a better understanding on how information is diffused on social networks. In this study, we focus on Twitter and we explore the impact of user behavior on their retweet activity. To represent a user’s behavior for predicting their retweet decision, we introduce 10-dimentional emotion and 35-dimensional personality related features. We consider the difference of a user being an author and a retweeter in terms of their behaviors, and propose a machine learning based retweet prediction model considering this difference. We also propose two approaches for matrix factorization retweet prediction model which learns the latent relation between users and tweets to predict the user’s retweet decision. In the experiment, we have tested our proposed models. We find that models based on user behavior related features provide good improvement (3% - 6% in terms of F1- score) over baseline models. By only considering user’s behavior as a retweeter, the data processing time is reduced while the prediction accuracy is comparable to the case when both retweeting and posting behaviors are considered. In the proposed matrix factorization models, we include tweet features into the basic factorization model through newly defined regularization terms and improve the performance by 3% - 4% in terms of F1-score. Finally, we compare the performance of machine learning and matrix factorization models for retweet prediction and find that none of the models is superior to the other in all occasions. Therefore, different models should be used depending on how prediction results will be used. Machine learning model is preferable when a model’s performance quality is important such as for tweet re-ranking and tweet recommendation. Matrix factorization is a preferred option when model’s positive retweet prediction capability is more important such as for marketing campaign and finding potential retweeters.

scholarly journals Political Humour in the Social Network Sites

2018 ◽  
Vol 6 (1) ◽  
pp. 70
Author(s):  
Ayşe Aslı Sezgin
Keyword(s):  
Social Network ◽  
Political Communication ◽  
Social Network Sites ◽  
The United States ◽  
Political Processes ◽  
Political Events ◽  
Political Views ◽  
The Social ◽  
Shared Social Values ◽  
The Arab Spring

“Social network sites” first began to be used as new tools of political communication during the 2008 Presidential Election in the United States, and their importance became even more apparent during the Arab Spring. In the course of this, the social network sites became a new and widely discussed channel of communication. In addition to its ability to bring together people from different parts of the world by removing any time and space barriers, creates a virtual network that allows individuals with shared social values to take action in an organized manner. Furthermore, this novel, versatile and multi-faceted tool of political communication has also provided a new mean for observing various aspects of social reactions to political events. Instead of voters expressing their political views through their votes from one election to the other, we nowadays have voters who actively take part in political processes by instantly demonstrating their reactions and by directly communicating their criticisms online.

scholarly journals LIFE ON DISPLAY: WHY IT IS IMPORTANT TO EXPOSE YOUR ACTIONS ON THE SOCIAL NETWORK

2021 ◽  
Vol 6(72) (4) ◽  
pp. 41-48
Author(s):  
A. E. Starchenko ◽  
M. V. Semina
Keyword(s):  
Higher Education ◽  
Social Networks ◽  
Social Network ◽  
Reference Group ◽  
Human Life ◽  
Sociological Study ◽  
The Social ◽  
Personal Accounts ◽  
The Impact ◽  
To Receive

Social networks have emerged relatively recently in human life, but have already become an integral part of it. Companies tell about themselves, their activities, innovations, promotions and events in their profiles. This helps increase audience coverage, tell more about your brand, products, services. People in personal accounts have the opportunity to share their lives and creativity through photos, videos and texts. Now it is not necessary to receive higher education to become an operator, director or actor whose talent is recognized by society. It is enough to start a page on the social network and start sharing your knowledge and creativity. To find out why people post photos, videos and write texts on their social networks, a pilot sociological study was carried out. The method of deep interview with active users of social networks was chosen to carry out the study. The interview allowed getting unique information, to learn the opinion of users about social networks, the impact of the new way of communication on their life, to identify the reasons why users start and maintain profiles. The respondents were 20 users of social networks between the ages of 19 and 22. Interviewees have profiles on the most popular Instagram and Vkontakte networks. As a result of the analysis of the interview, a tendency was revealed to differ in the perception of users of their actions on the social network and similar actions of other users. Their content is perceived by them as opportunities to be in sight, as a resource to form their social status and an element of influence on their reference group. And the same content published by others is perceived as boasting.

scholarly journals Academic Social Networks: How the web is changing our way to make and communicate researches

2015 ◽  
Vol 7 (2) ◽  
pp. 3-14 ◽  
Author(s):  
Giovanni Bonaiuti
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Sites ◽  
Rapid Evolution ◽  
Scientific Field ◽  
Academic Social Network ◽  
Academic Social Networks ◽  
Insight Into ◽  
The Web ◽  
Natural Component

Abstract Networking is not only essential for success in academia, but it should also be seen as a natural component of the scholarly profession. Research is typically not a purely individualistic enterprise. Academic social network sites give researchers the ability to publicise their research outputs and connect with each other. This work aims to investigate the use done by Italian scholars of 11/D2 scientific field. The picture presented shows a realistic insight into the Italian situation, although since the phenomenon is in rapid evolution results are not stable and generalizable.

Interactive radio, social network sites and development in Africa: a literature review study

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Marcos Komodromos
Keyword(s):  
Social Network ◽  
Literature Review ◽  
Mass Communication ◽  
Social Network Sites ◽  
Sub Saharan Africa ◽  
Agriculture Education ◽  
African Countries ◽  
Content Type ◽  
Study Results ◽  
The Impact

Purpose The technology determinism theory facilitated in assessing the impact of interactive radio and social network sites (SNSs) on development factors such as education, agriculture, health, and governance, by conducting an integrative and comprehensive literature review focusing on African countries. This paper aims to conduct this literature review to provide comprehensive empirical evidence on the impact of interactive radio and SNSs on development in Africa. Design/methodology/approach This study examined articles that were retrieved from online databases including EBSCOhost, Elsevier, Science Direct, SAGE Journals, Springer and Wiley Online Library. The keywords used included interactive radio, radio, development in Africa, SNS, agriculture, education, health, peace and governance. Search phrases were formulated using boolean operators “AND” and “OR.” Findings Study results revealed that interactive radio and SNSs improve knowledge among farmers and allow the dissemination of information on innovative agricultural techniques, which supports the adoption of sustainable practices. Interactive radio promotes political accountability because the strategies provide the voiceless and powerless communities with a platform to express themselves. This paper discovers that the incorporation of SNS with existing multimedia communication facilitates the dissemination of health-related information on illnesses such as Ebola, HIV, hypertension, diabetes and Polio, and interactive radio and SNS promote education among marginalized communities and under-served rural schools. Research limitations/implications The findings on the impact of interactive radio and SNSs do not represent all 54 countries in Africa. Although the studies included in this literature review were conducted in several countries such as South Africa, Nigeria, Somalia, Kenya, Malawi, Ghana, Tanzania, Uganda and Zambia, this limited the generalizability of the findings and recommendations. Also, the other potential limitation is that using the inclusion-exclusion criteria could have resulted in bias when selecting the studies to include in the review. Practical implications The paper might serve as a valuable source of information for students, academics and entrepreneurs where the impact of interactive radio and SNSs on agriculture, education, health and governance, which are core determinants of development in Africa, has been assessed for further case studies in this area. Social implications The use of interactive radio has helped in decreasing health issues caused by a deficiency in vitamin A among children in sub-Saharan Africa. Originality/value The development of sustainable and effective interactive radio programs is dependent on the collaboration of the core stakeholders such as governmental ministries, donor organizations and the mass communication sector. Numerous open sources on technology radio stations are available to employ social media managers to help in the application of knowledge.

The Impact of Social Networks on Science Students' Academic Performance in Ondo State Senior Secondary Schools, Nigeria

2021 ◽  
pp. 50-63
Author(s):  
Jethro Oludare OLOJO
Keyword(s):  
Social Networks ◽  
Academic Performance ◽  
Social Network ◽  
Science Students ◽  
The Social ◽  
Ondo State ◽  
Research Questions ◽  
Senior Secondary Schools ◽  
Senior Secondary ◽  
The Impact

The objective of this study was to examine the impact of social network usage on science students’ academic achievements in Ondo State’s senior secondary schools. The study was also to find the extent to which students under investigation used the social network platforms and the frequencies of their visits. In order to achieve this, a structured questionnaire was designed and administered to students from the three senatorial districts that made up the state. A multistage; which involved simple random and purposive sampling approaches was used to select the sample for the study. 150 copies of the questionnaire were distributed; out of which, 148 (98.78%) copies were returned. For the study, four research questions and two research hypotheses were developed. The hypotheses were assessed using the student's - t statistic at 0.05 significant level; using SPSS version 20 while the research questions formulated were evaluated using frequency counts and percentages. The study revealed that Ondo State senior secondary school science students can efficiently use the social network platforms for academic activities with male students being more proficient than their female counterparts. The study also revealed that the usage of social networks has assisted students to improve their academic performance; irrespective of their classes. Besides, the study showed that Facebook was the most popular of all the social network platforms. To this end, the researcher recommended that teachers, parents, and guidance should monitor the activities of their wards on the social network sites so that they can use the platforms to benefit their lots. Teachers should also use the advantage of students’ exposure to social networking to change their teaching methods from traditional one to online teaching.

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