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 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 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 Public Trolling Detection on Twitter Using Machine Learning

2021 ◽  
Vol 9 (VII) ◽  
pp. 3097-3100
Author(s):  
Miss. Pooja Dilip Dhotre
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Social Network ◽  
Social Networking ◽  
Social Networking Sites ◽  
Machine Learning Algorithms ◽  
The People ◽  
The World ◽  
Added Benefit ◽  
Current Popularity

Social media websites are among the internet's most far-reaching digital sites. Billions of social network users exist Users' frequent interactions with social networking sites, like Twitter, have a widespread and sometimes unfortunate effect on day-to-day life. Social networking sites make it easy for large amounts of unwanted and unrelated information to spread around the world. Twitter is a popular micro blogging service where users connect with others with similar interests. Because of the current popularity of Twitter, it is vulnerable to public shaming. Recently, Twitter has emerged as a rich source of human-generated information, with the added benefit of connecting you with customers and enabling two-way communication. It is generally accepted that when someone posts a comment in an occurrence, it is likely to humiliate the victim. The fact that shaming users' follower counts increase faster than that of the people who don't use shame is interesting. Using machine learning algorithms, users will be able to identify disrespectful words, as well as the overall negativity of those words, which is displayed in a percentage.

Social Media - A study to explore its Role and Contribution in Promoting Peace

2015 ◽  
Vol 9 (1and2) ◽  
Author(s):  
Mukta Martolia
Keyword(s):  
Social Media ◽  
Social Networking ◽  
Social Networking Sites ◽  
Northeast India ◽  
Human Interaction ◽  
Internet Technology ◽  
Religious Groups ◽  
The People ◽  
Use Of Social Media ◽  
The Arab Spring

In today’s world, the internet technology has grown widely, and social media have become a new platform to connect people. We see the use of social media to bridge the divides between different ethnic and religious groups and fostering inter-ethnic dialogues. Recently we have witnessed the Arab Spring, the Jan Lokpal Bill of Anna Hazare, and many such cases that have proved the power of social media. Thus, we can say that this was just the beginning of a wave, an era in the use of social networks to bring people together to fight and protest against violence. The power of social media cannot be ignored today. It has become essential and easy medium to reach a large number of audiences and has become a vital element of today’s life. The social media has proved itself to be a powerful tool for the promotion of peace and has provided not only national but international platform, which allows people to make a positive difference. Social media can be a powerful tool to mobilize people to build peace. With an estimation of around 200 million-plus blogs, more than 120 million YouTube videos and over 500 million Facebook users worldwide, we know that online social networking is a form of human interaction with enormous impact. It is a well-known fact that media affects the minds and behaviors of young people. If media and technology combined together, it can save lives. Thus, the main objective of the study was to evaluate the strength and weaknesses of social media as a tool in facilitating peace in Conflict Situation. The study also tried to analyze and figure out the contribution of social media in promoting peace and preventing violence. For the study various blogs were considered, who were working to bind the people of Northeast India together. Many social networking sites were studied as well to explore many facts.

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 Rumour Detection Models & Tools for Social Networking Sites

2019 ◽  
Vol 9 (2) ◽  
pp. 3291-3296
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Social Networking ◽  
Social Networking Sites ◽  
Early Stage ◽  
Economic Losses ◽  
Learning Approaches ◽  
The People ◽  
Social Media Platforms ◽  
Fuzzy Logic Technique

Efficient utilization of social networking sites (SNS) had reduced communication delays, at the same time increased rumour messages. Subsequently, mischievous people started sharing of rumours via social networking sites for gaining personal benefits. This falsified information (i.e., rumour) creates misconception among the people of society influencing socio-economic losses by disrupting the routine businesses of private and government sectors. Communication of rumour information requires rigorous surveillance, before they become viral through social media platforms. Detecting these rumour words in an early stage from messaging applications needs to be predicted using robust Rumour Detection Models (RDM) and succinct tools. RDM are effectively used in detecting the rumours from social media platforms (Twitter, Linkedln, Instagram, WhatsApp, Weibo sena and others) with the help of bag of words and machine learning approaches to a limited extent. RDM fails in detecting the emerging rumours that contains linguistic words of a specific language during the chatting session. This survey compares the various RDM strategies and Tools that were proposed earlier for identifying the rumour words in social media platforms. It is found that many of earlier RDM make use of Deep learning approaches, Machine learning, Artificial Intelligence, Fuzzy logic technique, Graph theory and Data mining techniques. Finally, an improved RDM model is proposed in Figure 2, efficiency of this proposed RDM models is improved by embedding of Pre-defined rumour rules, WordNet Ontology and NLP/machine learning approach giving the precision rate of 83.33% when compared with other state-of-art systems.

scholarly journals The use of social-networking sites in English language education: An exploratory study using SWOT analysis technique

2021 ◽  
Vol 58 (1) ◽  
pp. 4640-4650
Author(s):  
Sana Nazir Ahmed, Furrakh Abbas, Azhar Majeed Qureshi
Keyword(s):  
Social Media ◽  
Social Networking ◽  
Social Networking Sites ◽  
English Language ◽  
Swot Analysis ◽  
Language Education ◽  
Human Interaction ◽  
English Language Education ◽  
Learning And Teaching ◽  
Analysis Technique

The global importance of English as the language of international communication needs no description. English has gained competitive edge and is considered a requirement in order to make progress in the global world. There is bulk of research dedicated to finding better means of learning and teaching English language. The current research aims at exploring the potential of using social networking sites for improving English language skills especially in the skill areas of reading and writing. The research proposes to analyze the opinion of the participants by using SWOT analysis technique. This techniques dissects the themes from the data under strength, weakness, opportunity and threat in order to draw the picture of the potential of anything, In the current research, SWOT analysis technique was used to organize the data in the themes mentioned here. The study concludes that the use of social networking sites in English language education has marvelous potential as the students learn with ease of mind. The language is learnt in without any affective filters like anxiety or lack of motivation. Though social media sites can be effective platforms, their use may also distract the language learners with all their misinformation, ungrammatical content, and artificial human interaction. The study implicates that there is need to formulate effective strategies for proximal advantage of the strengths and countering the weaknesses and threats in order to make the best of the opportunities provided by social media sites in English language education.

A Comparative Analysis of Online Social Networking Sites and Their Business Models

E-Marketing ◽  
2012 ◽  
pp. 803-813 ◽  
Author(s):  
T. Andrew Yang ◽  
Dan J. Kim
Keyword(s):  
Social Networks ◽  
Comparative Analysis ◽  
Social Networking ◽  
Web Sites ◽  
Online Social Networks ◽  
Social Networking Sites ◽  
Business Models ◽  
Online Social Networking ◽  
New Business ◽  
Revenue Models

In the world of e-marketing, new business models are introduced to accommodate changes caused by various factors, including the markets, the services, the customers, among others. One latest trend of e-marketing is social networking Web sites, many of which have attracted not only large number of users and visitors, but also business companies to place their online ads on the sites. As an important example of Web 2.0 applications, online social networks deserve comprehensive studying and analysis; they are not only employed as an effective vehicle of e-marketing, but may impact how future Web-based applications would be developed. In this chapter, we explore online social networking as a new trend of e-marketing, by conducting a comparative analysis of online social networking sites. We first discuss the various types of online social networks, based on the classification by Laudon & Traver (2008), and then analyze online social networks from a business strategy point of view, by discussing the primary revenue models for online social networking sites. The primary contribution of this chapter is a comparative analysis and discussions of representative online social networking sites and their respective revenue model(s). This chapter aims to provide the reader with a basic understanding of the emerging online social networking Web sites and their primary revenue models.

scholarly journals Content Filtering of Social Media Sites Using Machine Learning Techniques

2021 ◽  
Author(s):  
U.S. Tambe ◽  
N.R. Kakad ◽  
S.J. Suryawanshi ◽  
S.S. Bhamre
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Social Networking ◽  
Social Relations ◽  
Online Social Networks ◽  
Social Networking Sites ◽  
Machine Learning Techniques ◽  
Content Filtering ◽  
Learning Techniques ◽  
Personal Interests

To build a social network or social relations between people, we use social networking platforms like Facebook, Twitter, apps, etc. Using this media, users can share their views and opinions about a particular thing. Many people use their media for personal interests, entertainment, the market stocks, or business purposes. Nowadays, user security is the major concern for social networking sites. Online social networks give a little bit of support regarding content filtering. In this article, we proposed a system that provides security regarding malicious content that is posted on their social networking sites. To filter the content that might be unwanted messages, labeled images, or vulgar images, we proposed three level architecture. The user can use the auto-blocking facility as well.

Sign in / Sign up

Export Citation Format

Share Document