Online Social Sites Research Articles

Do Youngsters Reflect the ‘Fake or Real’ Identity, Personality, and Emotion on Facebook?

Abstract: The sophisticated technology has the potential to integrate with social media. Hence, online social sites become a medium for youngsters’ tendency to express their appearance, identity, and narcissism. Consequently, the current study aimed to investigate the reflection of fake or real identity, personality, and emotion of Indonesian teenagers used on social media Facebook. To attain the objective of the study, qualitative descriptive was used as a research design. The data was obtained from youngsters’ posts on Facebook in the range of 2018-2019. The instrument used in gathering the data was Virtual Advertising Operations (VOA). The total data was 1473 posts. In analyzing the data that have been classified based on the three categorizations, we employed AntConc application. The findings show that youngsters express their fake personality, identity, and emotion through Facebook features in terms of style theme with several subthemes followed by spectrums and issues. On the other hand, it could be inferred that youngsters show their identity, personality, and emotion on social media Facebook based on their level of relationship. Further, future research directions on the identity, personality, and emotion of Indonesian youngsters on Facebook are discussed. Keywords: Emotion, Facebook, Identity, Personality, Youngster

Fake Accounts Identification in Mobile Communication Networks Based on Machine Learning

Fake accounts on online social networks are increasing today with an increase in the number of active social network users. Social media websites allow users to share thoughts, facts, views and re-sharing these into various networks. Social media platforms provide users with enormous valuable information but with this great amount of information in social media, many issues like fake profile, online hacking have also grown. The fake profiles in online social sites create fake news and share unwanted material which contains spam links that affect natural users. The massive issue in social media communication networks is spam and it is necessary to identify fake profiles to stop spam. In this paper, a supervised machine learning algorithm called support vector machine (SVM) is used to identify fake accounts on social media effectively. In order to automatically identify fake online profiles, Random Forest classifier is used with SVM. With this concept, it can be applied online easily to identify millions of accounts that cannot be examined manually. The result of this model is compared with other identification techniques and the results show that the proposed algorithm performs better with high precision and recall. This method efficiently safeguards social media networks from online threats and attacks.

Online Advertising's Potential Impact on Consumers

Online advertising is a type of promotion that uses the Internet and World Wide Web to deliver marketing messages in order to attract, retain, and enhance customers. A consumer can have an idea and information about products and services from a small business enterprise as well as a large business enterprise. Focus has also been placed on various trends in online advertising, which has resulted in the fact that online ads have become a challenge for print ads, as various online applications and social sites help to lead to data more quickly than other existing advertisement mediums. This is an appealing awareness-raising tool for business promotion. Online advertising is a thriving industry that is being researched.

An Efficient LSTM Model for Fake News Detection

Information spread through online social media or sites has increased drastically with the swift growth of the Internet. Unverified or fake news reaches numerous users without concern about the trustworthiness of the info. Such fake news is created for political or commercial interests to mislead the users. In current society, the spread of misinformation is a big challenge. Hence, we propose a deep learning-based Long Short Term Memory (LSTM) classifier for fake news classification. Textual content is the primary unit in the fake news scenario. Therefore, natural language processing-based feature extraction is used to generate language-driven features. Experimental results show that NLP-based featured extraction with LSTM model achieves a higher accuracy rate in discernible less time.

Effects of Social Media on Consumer Behaviour for Tourism Products

The study helps to investigate the relationship between social media and consumer behavior regarding tourism products. Every consumer is using social media and they are getting information from online media and social sites. Communication through online media and social applications is getting easy and less expensive. Social media affects customers’ purchasing behavior. Electronic word of mouth is also a part of social media that influences consumers’ decision process. This is a review paper that helps to understand information sharing in social media in the tourism industry. This paper helps to understand the effects of information-based social applications and online media on consumer behavior in tourism sector and also identify the most important variable which influences consumer behavior in tourism.

Hate speech in intercultural encounters

The issue of hate speech has been a topic of international debate—most frequently in the domains of law, philosophy and language. Different issues linked to changes in society, ranging from the proliferation of social media, innovation and technology and influx of fake news, disinformation and propaganda to the rise of nationalism, far-right movements, increased cross-border movement of people and transnational business have made studying the conceptual and practical aspects of hate speech in different contexts ever more important. The papers in this issue focus on the sociolinguistic aspects of the use of hate speech and its different variants in online communication, offering a much-needed perspective on how hate speech in digital communication can be identified and tackled. For example, Dr. Manana Ruseishvili and Dr. Rusudan Dolidze analyse hate speech in computer-meditated communication, focusing on the polylogal, asynchronic remarks made by members of the public reacting to articles in online media or press releases about the LGBT pride event planned for June 2019. The research carried out by Lilit Bekaryan explores how hateful posts and comments can start among Facebook users, and studies the language means employed in their design based on data from more than ten open Facebook pages managed by popular Armenian figures, such as media experts, journalists, politicians and bloggers. Dr. Tatjana R. Felberg explores the interconnectedness between impoliteness and hate speech in online comments in Croatia and Serbia by applying impoliteness theory and a critical discourse analysis framework. Her research demonstrates that those who post often fluctuate between hate speech and impoliteness. Dr. Ayunts and Dr. Paronyan provide a comparative analysis of manifestations of hate speech and euphemisms in Armenian and British online media outlets and social sites targeting people's sexual orientation with emphasis on the interconnectedness of hate speech and culture. This issue was prepared as part of the project ‘Intercultural encounters in academia and work places in South Caucasus and Norway’ funded by DIKU, the Norwegian Agency for International Cooperation and Quality Enhancement in Higher Education. The project partner universities are Oslo Metropolitan University, Ivane Javakhishvili Tbilisi State University, Yerevan State University and Khazar University.

From Euphemism to Verbal Aggression in British and Armenian Cultures


 The topic of the present article concerns verbal aggression and focusses on the verbal expression of the emotional mind; specifically, the expression of negative feelings, emotions and attitudes. Since computer-mediated communication is widely used to shape and reshape public opinion, the analysis of hate speech on the material of internet discourse may shed light on the manipulative communicative tactics that are used in online media and social networking sites to spread hostility and negativity globally. Hence, the examination of the language strategies and tactics that are used to formulate hate speech becomes essential in communicatively oriented linguistic studies.
 
 
 The present article provides a comparative analysis of manifestations of hate speech and euphemisms in Armenian and British online media outlets and social sites targeted towards people's sexual orientation. The aim of the paper is to show the close connection between hate speech and culture. The research, which embarks on two basically different cultures – British and Armenian – is carried out within the framework of cross-cultural pragmatics and discourse analysis. A qualitative research method is applied to analyse samples of hate speech. Social sites and online media outlets were searched through search engines, using certain keywords (LGBT, sexual minorities, etc.). For the purpose of the study, language resources from English and Armenian – words, expressions, constructions, speech acts expressing hostile attitudes towards sexual orientation – have been picked out and analysed.

Restriction Algorithm for Duplicate Posts on Online Social Networks: Facebook

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

Determinants of Users Attitudes towards Social Websites Banner Advertising among University Students in Ethiopia

Social websites (SWSs) have quickly developed in notoriety and user’s acceptance comprehensively. Especially in recent years, they have become the fundamental spot for social relation, conversation, and correspondence. Today, numerous organizations promote their items on online social websites. The present study evaluates the impacts of social website on Ethiopian university students’ beliefs and concerns of social website advertising (SWA) on their attitudes toward social website advertising and social websites banner advertisement clicking behavior. Information was gathered from a sample of 337 university students of five private colleges/university in Addis Ababa Ethiopia. Results shows the beliefs of social website advertising promoting as useful and engaging effectively affect client mentalities toward informal community publicizing and their advertisement clicking behavior. Likewise, client worry of social website advertising as aggravating has a beneficial outcome on both their social website advertising and advertisement clicking behavior. Further aggravation and offensive were seen as emphatically affecting advertisement clicking conduct of Ethiopian higher institution student’s behavior towards SWA. The general outcomes shows that valuable and fascinating parts of social website advertising in Ethiopian higher institution students’ viewpoint were shown to make social website advertising compelling.

A Study of Social Information Seeking (SIS) among LIS Research Scholars in Pakistan

Purpose: There is ample evidence that students and teachers often seek academic information using participatory online social sites (POSS). The purpose of this study is to explore the intent of social information seeking (SIS) among library & information science research students in Pakistan. The study also attempts to examine the relationship between change in information behaviour and information retrieval strategies while seeking information from online social spaces. The influence of online collaboration in the use of social media was also examined. Methodology: Quantitative research method was used to conduct this study. Data was collected from 123 research (MPhil & PhD) students currently enrolled in seven postgraduate library schools in Pakistan. The data was gathered using survey questionnaire (using 5-point Likert scale items), administered both in print format and online through Google Form. SPSS version 19 was used to analyse the data. Findings: Major findings of this study were that there is a strong positive correlation between SIS and change in the overall information behaviour of research students. Majority of participants responded that social websites help in reshaping the information behaviour in a collaborative environment thus contributing to upsurge the SIS practices among research students. The study also found that LIS research scholars in Pakistan prefer to consult interactive websites more than social media spaces for academic information. Gender has been an influencing variable in SIS practices, however, time spent and frequency of using POSS does not affect one’s SIS practices. Originality: Social Information helps people to connect with each other and is comparatively a new concept in the field of Information Seeking Behaviour. This is the first study on SIS with respect to LIS research students in Pakistan.

Social Computing

This article explores the influence of social, self, and use factors on the intention to perform social computing actions in online social sites. A survey was conducted using peer-to-peer file sharing as representative of a social computing action. Collected data was analyzed using the structural equation modeling method with partial least squares. These findings show that social computing consensus and social computing cooperation are important social factors that have significant influence on the formation of social norms, which in turn increases the intention of members to perform social computing actions. Interestingly, the widely tested use factors perceived usefulness and perceived ease of use have no significant effect upon a user's intention to perform social computing actions. Furthermore, while social norms have significant influence upon a user's intention to perform social computing actions, self-identity has no significant impact. These findings lead to academic and practical implications on the efficacy of social, self, and use factors in furthering understanding of social computing.

Social Network with Dynamic Identity-based Broadcast Encryption using Security Tree

In this paper, we suggest the security tree scheme using dynamic identity-based broadcast encryption, using this scheme, it is possible to parted a message to many linked nodes and represent these nodes as security tree and give every receiver permission to read special linked nodes from security tree. General Terms Online Social Website is stretched over worldwide such as Facebook, Linked In; and then there are many security threats by attackers. In addition because sensitive data is concentrated on the central server, privacy can by expose to SNS provider as well as malicious users. To overcome this problem, many previous researches suggest data may not be stored in central server. When a user transmits a message, then server does not interfere with the process. Thus, the user who transmits a message needs way to message thee key that are used to message the key that are used for message encryption scheme.

Social exchange in online social networks. The reciprocity phenomenon on Facebook

Social exchange theory proposes that social behavior is the result of an exchange process. The purpose of this exchange is to maximize benefits and minimize costs. Online social networks seem to be an ideal platform for social exchange because they provide an opportunity to keep social relations with a relatively low cost compared to offline relations. This theory was verified positively many times for offline social interactions, and we decided to examine whether this theory may be also applied to online social networks. Our research is focused on reciprocity, which is crucial for social exchanges because humans keep score, assign meaning to exchanges, and change their subsequent interactions based on a reciprocity balance. The online social network platform of our choice was Facebook, which is one of the most successful online social sites allowing users to interact with their friends and acquaintances. In our study we found strong empirical evidence that an increase in the number of reciprocity messages the actor broadcasts in online social networks increases the reciprocity reactions from his or her audience. This finding allowed for positive verification of the social exchange theory in online communities. Hence, it can be stated that our work contributes to theories of exchange patterns in online social networks.

Quantifying Political Behavior on Mobile Devices over Time: A User Evaluation Study

The way citizens use technology has changed dramatically in just the last decade; nearly one-third of American adults own tablets, and almost a half own smartphones. But it is not just ownership that is on the rise; citizens are increasingly using such technology to communicate about and participate in politics. The present study utilized a multimethod approach to tap into how technology affects citizens’ political behaviors online in the context of the 2012 U.S. Presidential primary season. Compiling survey data with tablet-tracking behavior in a field experiment, results showed that users spent more days with online aggregators (such as Google and Yahoo), recreational sites (like games), and social interaction sites than news and politics. But when they did spend time with news and politics, they spent an average of 10 minutes on each news page, and national/regional news was the most visited subtopic. User-specific descriptive analyses provide portraits of each user’s demographic makeup and online political behavior. Finally, we linked user ideology to user behavior through accurate, real-time behavioral observations. Results suggest that participants are more likely to view news from their own ideological perspective than the other, demonstrating evidence for selective exposure.

Why recommend a brand face-to-face but not on Facebook? How word-of-mouth on online social sites differs from traditional word-of-mouth

We examine the conceptual difference between consumer electronic word-of-mouth on online social sites (sWOM) such as Facebook and traditional face-to-face word-of-mouth (WOM). We find that consumers are less willing to engage in sWOM than WOM. Such a difference in willingness to offer word-of-mouth can be explained by social risk associated with different communication modes. We show that the difference between people's desire to engage in sWOM and WOM is mediated by perceived social risk and amplified when social risk is made salient. Furthermore, we show that consumers' need to self-enhance mitigates the difference in willingness to offer sWOM versus WOM.

‘Freedom’ and ‘Social Responsibility’ of Social Media: Emerging Issues in the Indian Legal System

The paper seeks to highlight the performance of social responsibility as regards the online social sites. The role of social networking sites as a replacement to the erstwhile ‘open access’ platforms of deliberations will also be addressed. This paper also analyses various laws regulating the freedom of speech and expression in this open, wide cyberspace. It advocates the need for redefining the basic concepts of ethics, morality, freedom, liberty, and responsibility, which form the basis of legal framework regulating this large contiguous cyberspace.

English

With the growing popularity of Internet communication applications among adolescents, the Internet, online social sites, instant messaging and cell phones have become an important social tool for their development. For adolescents who perceive low friendship quality, Internet use for communication purposes predicted less depression, whereas Internet use for non-communication purposes predicted more depression and more social anxiety. This study examined teens’ use of social interactive technologies and the role that social anxiety plays on how adolescents communicate with others (technology or face-to-face). The questionnaire was prepared to apply in Afyonkarahisar, Manisa and Usak cities in order to measure any relationship between social anxiety and choise of communication options among adolescents. Questionnaire datas were gathered from High School adolescents (ranged from 15-18; freshman, sophomore, junior and senior) included 544. Adolescents almost don’t use messanger sites and mail address. They generally use instant message with their cell phones. They spend 1-2 hours for a day by listening music and avarage 30 minutes during the day by using Facebook. More than half of teens have cell phones that able to call, message and access to Internet. The findings of the current study found that females are using text messaging more than males. However, males are playing games for a long time than females. In addition, females are feeling more uncomfortable talking with others face-to-face than males. And, females also prefer talking with some on computer instead of talking face-to-face than males. Similarly, females prefer making new friends with someone on computer more than males. Keywords: Social Anxiety, Communication Tools, Technology, Adolescents

Analysis of misinformation containment in online social networks

With their blistering expansion in recent years, popular online social sites such as Twitter, Facebook and Bebo, have become not only one of the most effective channels for viral marketing but also the major news sources for many people nowadays. Alongside these promising features, however, comes the threat of misinformation propagation which can lead to undesirable effects. Due to the sheer number of online social network (OSN) users and the highly clustered structures commonly shared by these kinds of networks, there is a substantial challenge to efficiently contain viral spread of misinformation in large-scale social networks. In this paper, we focus on how to limit viral propagation of misinformation in OSNs. Particularly, we study a set of problems, namely the βTI-Node Protectors problems, which aim to find the smallest set of highly influential nodes from which disseminating good information helps to contain the viral spread of misinformation, initiated from a set of nodes I, within a desired fraction (1-β) of the nodes in the entire network in T time steps. For this family of problems, we analyze and present solutions including their inapproximability results, greedy algorithms that provide better lower bounds on the number of selected nodes, and a community-based method for solving these problems. We further conduct a number of experiments on real-world traces, and the empirical results show that our proposed methods outperform existing alternative approaches in finding those important nodes that can help to contain the spread of misinformation effectively.

Twitter, MySpace, Digg

Sentiment analysis is a growing area of research with significant applications in both industry and academia. Most of the proposed solutions are centered around supervised, machine learning approaches and review-oriented datasets. In this article, we focus on the more common informal textual communication on the Web, such as online discussions, tweets and social network comments and propose an intuitive, less domain-specific, unsupervised, lexicon-based approach that estimates the level of emotional intensity contained in text in order to make a prediction. Our approach can be applied to, and is tested in, two different but complementary contexts: subjectivity detection and polarity classification. Extensive experiments were carried on three real-world datasets, extracted from online social Web sites and annotated by human evaluators, against state-of-the-art supervised approaches. The results demonstrate that the proposed algorithm, even though unsupervised, outperforms machine learning solutions in the majority of cases, overall presenting a very robust and reliable solution for sentiment analysis of informal communication on the Web.

Investigating the use of social networking sites and their implications for HIV/Aids communication amongst Rhodes University students

The rise and dominance of social networking sites has generated increasing interest amongst scholars, mainly to understand their nature and the activities supported by these social sites. Studies conducted on social networking sites have generated information on the potential of such sites in boosting revenue-generating businesses, with limited research on how online sites can be used to address the social challenges faced by societies today. This article maintains that online social sites, in particular HIV/Aids-related sites, can possibly be used for HIV/Aids communication. The article therefore presents and reflects on the use of social networking sites amongst Rhodes students and the implications for HIV/Aids communication. The concept ‘use’ in this article is discussed under three sub-topics: (1) extent of social network site use; (2) topics or issues discussed on social sites focusing on HIV/Aids issues; and (3) the advantages and challenges of using social sites to communicate about issues such as HIV and Aids. Using both quantitative and qualitative approaches to the research design and methodology, the study found that social networking sites have become part of the youth's everyday activities, with social sites focusing on HIV/Aids-related issues being used as platforms for learning about the disease, sharing personal experiences and even finding encouragement from peers facing similar challenges. Drug abuse and sexual debut are amongst the topics discussed on HIV/Aids sites. The study also reveals that the effectiveness of social sites in communicating about HIV/Aids can be downplayed by issues of privacy, artificiality and the nature of relationships within networks.