Online Social Networks: Online Social Networking Platforms, Online Social Media

2014 ◽  
pp. 1209-1209 ◽  
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Networking ◽  
Online Social Networks ◽  
Online Social Networking ◽  
Online Social Media

scholarly journals A Trigger or a Muffler? - Examining the Dynamics of Crosscutting Exposure and Political Expression in Online Social Media

2013 ◽  
Vol 5 (1) ◽  
pp. 16-27
Author(s):  
Soo Young Bae
Keyword(s):  
Social Media ◽  
Social Networking ◽  
Online Social Networks ◽  
Social Networking Sites ◽  
Social Networking Site ◽  
Online Social Networking ◽  
Political Expression ◽  
Online Social Media ◽  
Candidate Support

This study explores the potential of online social media to serve as a sphere for political discourse and investigates the extent to which everyday uses of online social networking sites can expose citizens to politically diverse viewpoints.  In addition, this study asks whether such crosscutting exposure in online social networks will act as a trigger or a muffler for political expression – that is, whether exposure political difference will stimulate or discourage political discussions.  With analyses of a sample of online social networking site users in the context of the 2012 presidential election in South Korea, this study explicates the link between crosscutting exposure and citizens’ political expressions in social media.  Results reveal that contrary to the predictions in previous literature, exposure to politically incongruent viewpoints in online social networking sites does not seem to undermine users’ expressive behaviors but instead positively contribute to political expression.  In addition, this study shows the significant role of citizens’ perceptions of candidate support in their own networks, and illustrates that the dynamics of political expression differ significantly depending on the users’ age.

scholarly journals Restriction Algorithm for Duplicate Posts on Online Social Networks: Facebook

2020 ◽  
Vol 6 (1) ◽  
pp. 33-38
Author(s):  
Babe Sultana ◽  
Md Nasir Hossain Hridoy ◽  
Mohammad Mohitul Islam ◽  
Ruhul Amin ◽  
Farzana Rahman
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Networking ◽  
Online Social Networks ◽  
Computation Time ◽  
Research Paper ◽  
Social Networking Site ◽  
Second Step ◽  
Online Social Networking ◽  
Science And Engineering

Duplicate content or writing on online social networks is a material that shows up in many more than one location on Online Social Site, Pages etc. Nowadays Facebook is an online social networking site that connects people together during the form of expressing personal preferences and opinions as well as communication. In this research paper, we found detecting duplicate material in Facebook groups, pages, and trying to provide a solution for limiting this duplicate content, that is being posted to Facebook and other online social networks. We specified the solution to the issue in the first step and designed an algorithm called Restriction Algorithm for Duplicate Content, which is restricted to posting the copied content in more times on social networks like Facebook. In the second step, we have implemented it to validate our methodology and we have checked the identification of duplicate content of social media writing by using various social media posts as input tests and finally enriching the findings at a satisfactory stage. With optimal computation time, our proposed algorithm can handle large string sizes (more than 10,000 bytes). GUB JOURNAL OF SCIENCE AND ENGINEERING, Vol 6(1), Dec 2019 P 33-38

scholarly journals PERILAKU VIRTUAL REMAJA: STRATEGI COPING, HARGA DIRI, DAN PENGUNGKAPAN DIRI DALAM JEJARING SOSIAL ONLINE

2017 ◽  
Vol 16 (2) ◽  
pp. 128
Author(s):  
Naufal Mafazi ◽  
Fathul Lubabin Nuqul
Keyword(s):  
Social Media ◽  
Social Networking ◽  
Coping Strategies ◽  
Online Social Networks ◽  
Self Esteem ◽  
Online Social Networking ◽  
Self Disclosure ◽  
Ways Of Coping ◽  
Active User ◽  
Sample Characteristics

Teenager’s activities in the online social networks, influenced by the nature of teenager’s characteristic who tends to look for a good impression from others. This study examined the effects of coping strategies and self-esteem on the teenagers’ self-disclosure on online social networking. In total, 185 adolescents participated the study; they were identified using the purposive sampling. The sample characteristics were having a social media account and an active user of social media. The Revised Self-Disclosure Scale, the Self-Esteem Scale, and the Ways of Coping Checklist were used to collect data.  The results of regression analysis showed that there is a positive and significant correlation of coping strategies and self-esteem on adolescents’ disclosure in online social networking.

scholarly journals ANALYSIS OF VARIOUS APPROACHES OF ABUSIVE TEXT DETECTION IN ONLINE SOCIAL NETWORKS

2021 ◽  
pp. 124-130
Keyword(s):  
Social Media ◽  
Social Networking ◽  
Online Social Networks ◽  
Social Networking Sites ◽  
English Language ◽  
Research Work ◽  
Accurate Method ◽  
Online Social Networking ◽  
The People ◽  
Language Constructs

Social media is one of the most influential tool for sharing information across different regions among different users .The people sharing their interests in various aspects in online social networking platforms like Facebook, twitter etc. Therefore the usage of hate text steadily increasing. Nowadays it has been reviled unfair behavior of the users in social networking sites. The existence of abusive text on different online social networking platforms and identification of such text is a big challenging task. To understand the complexity of language constructs in different languages is very difficult .Already lot of research work has completed in English language. This paper gives detail analysis of detecting hate text in various languages Hindi, urdu, Arabic, Bengali, Telugu. We incorporated various kinds of ML and DL based algorithms to identify hate text in OSN’s. A review is done related to different classifiers where a comparison made between different models of ML, DL algorithms. Finally finds the accurate method to classify the text is offensive or not by finding the parameters i.e. accuracy and F1score

scholarly journals Detect Extreme Sentiments on Social Networks using BERT

2021 ◽  
Author(s):  
Muhammad Luqman Jamil ◽  
Sebastião Pais ◽  
João Cordeiro ◽  
Gaël Dias
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Public Opinion ◽  
Social Network ◽  
Social Networking ◽  
Online Social Networking ◽  
Social Media Data ◽  
Preceding Work ◽  
Unsupervised Approach ◽  
Media Data

Abstract Online social networking platforms allow people to freely express their ideas, opinions, and emotions negatively or positively. Previous studies have examined user’s sentiments on these platforms to study their behaviour in different contexts and purposes. The mechanism of collecting public opinion information has attracted researchers to automatically classify the polarity of public opinions based on the use of concise language in messages, such as tweets, by analyzing social media data. In this paper, we extend the preceding work [1], by proposing an unsupervised approach to automatically detect extreme opinions/posts in social networks. We have evaluated our performance on five different social network and media datasets. In this work, we use the semi-supervised approach BERT to check the accuracy of our classified dataset. The latter task shows that, in these datasets, posts that were previously classified as negative or positive are, in fact, extremely negative or positive in many cases.

Working Adults' Buying Intention Through Online Social Network

2021 ◽  
Vol 17 (4) ◽  
pp. 92-116
Author(s):  
Syed Shah Alam ◽  
Chieh-Yu Lin ◽  
Mohd Helmi Ali ◽  
Nor Asiah Omar ◽  
Mohammad Masukujjaman
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Online Social Networks ◽  
Perceived Risk ◽  
Word Of Mouth ◽  
Online Social Network ◽  
Perceived Value ◽  
Online Social Media ◽  
Starting Point

Most businesses have online social media presence; therefore, understanding of working adult's perception on buying through online social networks is vital. The aim of this study is to examine the effect of perceived value, sociability, usability, perceived risk, trust, and e-word-of-mouth on buying intention through online social network sites. The research model for this study was developed based on the literature on information system research. This study adopted convenient sampling of non-probability sampling procedure. Data were collected through self-administered questionnaire, and PLS-based path analysis was used to analyse responses. The findings of the study shows that perceived value, sociability, usability, e-word-of-mouth, attitude, and subjective norm are significant constructs of buying intention through online social networks. This research can serve as a starting point for online shopping research through online social media while encouraging further exploration and integration addition adoption constructs.

Improving the organizational knowledge sharing through online social networks

Kybernetes ◽  
2019 ◽  
Vol 49 (11) ◽  
pp. 2615-2632
Author(s):  
Bo Yang ◽  
Lulu Wang ◽  
Bayan Omar Mohammed
Keyword(s):  
Social Networks ◽  
Social Networking ◽  
Knowledge Sharing ◽  
Online Social Networks ◽  
Social Networking Sites ◽  
Employee Motivation ◽  
Organizational Knowledge ◽  
Online Social Networking ◽  
Content Type ◽  
The Impact

Purpose Social technologies can offer a strong means for organizations to manage their information flows and thus make changes on the organizational knowledge sharing, which may then be linked to employees’ productivity and performance enhancements. The purpose of this paper is to predict the impact of using the online social network on employee motivation and employee motivation effects on organizational knowledge sharing. Design/methodology/approach From employees of tax affairs organization, data are collected. For evaluating the model’s elements, a questionnaire was designed. It was revised by experts with significant experiences. For statistical analysis, SMART-PLS 3.2 is used. Findings Findings have confirmed the validity of the proposed model. The results also have indicated that online social networks, social trust and social goals have a positive and important impact on employee motivation. Furthermore, obtained results have revealed that organizational knowledge sharing is significantly influenced by employee motivation and organizational commitment. Research limitations/implications The study contributes to the literature on organizational knowledge sharing and employee motivation in online social networking sites. Organizations could benefit from this knowledge by accepting that social networking sites must be considered as a critical component of the knowledge sharing, and precise targeting efforts could be directed for those users. Also, it could be exciting to study further factors affecting the development of organizational knowledge sharing in larger organizations. Originality/value The paper rises the understanding of what online social networking encompasses and how it can be utilized for the organization. The ideas and discussion are similarly applicable to libraries and may give them new visions into the delivery of social networking applications as part of their facilities to users.

scholarly journals Social networking services analysis: main challenges and application areas.

2020 ◽  
Vol 11 (8-2020) ◽  
pp. 192-196
Author(s):  
A.L. Shchur ◽  
◽  
I.O. Datyev ◽  
A.M. Fedorov ◽  
◽  
...  
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Networking ◽  
Online Social Networking ◽  
Social Networking Services ◽  
The World

Online social networking services are one of the most popular types of social media in the world. The report discusses some areas of research built on the use of information obtained from social networks, as well as the main difficulties that arise during the extraction of these data arrays.

scholarly journals Filtering unwanted posts from online social networks (OSN)

2021 ◽  
Vol 10 (3) ◽  
pp. 1599-1602
Keyword(s):  
Social Networks ◽  
Social Networking ◽  
Online Social Networks ◽  
Personal Space ◽  
Online Social Networking ◽  
Important Thing ◽  
On Line ◽  
Index Terms ◽  
Textual Content ◽  
Filtering Procedure

Now a days, unexpectedly growing using on-line social networks (OSNs). Through this offerings user’s can speak and switch any data. The important thing downside of those Online Social Networking (OSN) offerings is the dearth of privateness for the user’s personal space. We use sample matching and textual content class set of rules for correct filtering results. We suggest a gadget permitting OSN customers to own a right awaymanages at the messages published on their walls. It might be a bendy region that rule primarily based totally gadget are used to lets in customers to customize the filtering procedure implemented to their user’s profiles. A system gaining knowledge of method robotically labeling messages in help of content-primarily based totally filtering. Index Terms: content-primarily based totally filtering, filtering rule, filtering gadget, system gaining knowledge of, on-line social networks

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