• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1626-1638
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• 2019

Social Networking Sites (SNS) provide people with unique online social interaction environments where users can disclose their thoughts, feelings, and opinions to their personal contacts. Although previous studies have suggested that such activities produce positive effects on SNS user well-being, this study considered potential negative effects by investigating the relationship between SNS use and depression. In particular, This stydy examined how specific activities are related to different types of social comparison (upward/downward/horizontal) and how these different types of social comparison influence depressed moods among college students. The analysis of a survey of 245 Instagram users found that (1) looking at other people's status updates and commenting on other people's photos influences upward social comparison, (2) frequency of Instagram use predicts upward/downward/horizontal social comparison, and (3) upward social comparison was postively associated with depression, while downward social comparison was negatively associated with depression. Furthermore, the path anlaysis show that social comparison mediates the effect of Instagram use on depression. It suggests that Instagram use does not directly increase depression but it can lead to depression when social comparison on Instagram triggers depression.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.243-253
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• 2023

Social television encompasses the social media aspect of television viewing. This study attempts to investigate how social television influences Hispanic and national ethnic identification as well as social presence. Based on the theoretical framework of Tajfel and Turner's Social Identity Theory (SIT), this study focuses on the potential influence of social television on Hispanics' ethnic identifications and social presence. With a sample of 100 Hispanic students, we conducted a lab experiment to measure the effects of exposure to ethnic and non-ethnic related Twitter feeds on Hispanic and national ethnic identification along with social presence. Findings reveal that there was no significant difference between those exposed to the ethnic-identity related Twitter feed compared to those exposed to the non-ethnic identity related Twitter feed, followed by the control group not exposed to the Twitter feed at all. Implications were discussed.

• International Journal of Knowledge Content Development & Technology
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• v.7 no.4
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• pp.5-26
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• 2017

A cross-cultural comparison of social networking structure on McDonald's Facebook fan sites between Taiwan and the USA was conducted utilizing the individualism/collectivism dimension proposed by Hofstede. Four network indicators are used to describe the network structure of McDonald's Facebook fan sites: size, density, clique and centralization. Individuals who post on both Facebook sites for the year of 2012 were considered as network participants for the purpose of the study. Due to the huge amount of data, only one thread of postings was sampled from each month of the year of 2012. The final data consists of 1002 postings written by 896 individuals and 5962 postings written by 5532 individuals from Taiwan and the USA respectively. The results indicated that the USA McDonald's Facebook fan network has more fans, while Taiwan's McDonald's Facebook fan network is more densely connected. Cliques did form among the overall multiplex and within the individual uniplex networks in two countries, yet no significant differences were found between them. All the fan networks in both countries are relatively centralized, mostly on the site operators.

• Journal of Digital Contents Society
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• v.16 no.4
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• pp.565-573
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• 2015

The development of social media in the 2000s led the unspecified individuals to band together for common interests. Social networking services served as a far-reaching tool for sharing different thoughts and interpretation of the pop culture and helped people build up close relations driven by their common interests for certain works of the pop culture. This Study introduces the TV Series as a case that displays specific patterns of communication between its producer and viewers. Producer Bryan Fuller of the Series as well as key production staffs were quite active on social networking sites with the understanding of what the audience desired and the willingness to sympathize with them, which were eagerly welcomed by the dedicated audience whose number, though, was not big. For the Hannibal production team, SNS was a means for them to just be consumers who appreciate the work instead of solely being the content provider. Their approach is quite different from unilateral marketing approaches employed in the past. Through this case, the Study aims to suggest that social networking sites serve as a powerful medium connecting producers and viewers or as an information hub, and that how interactive contents shall be delivered in the new media environment to be effective.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.112-119
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• 2023

Traditionally used for networking computers and communications, the Internet has been evolving from the beginning. Internet is the backbone for many things on the web including social media. The concept of social networking which started in the early 1990s has also been growing with the internet. Social Networking Sites (SNSs) sprung and stayed back to an important element of internet usage mainly due to the services or provisions they allow on the web. Twitter and Facebook have become the primary means by which most individuals keep in touch with others and carry on substantive conversations. These sites allow the posting of photos, videos and support audio and video storage on the sites which can be shared amongst users. Although an attractive option, these provisions have also culminated in issues for these sites like posting offensive material. Though not always, users of SNSs have their share in promoting hate by their words or speeches which is difficult to be curtailed after being uploaded in the media. Hence, this article outlines a process for extracting user reviews from the Twitter corpus in order to identify instances of hate speech. Through the use of MPCA (Modified Principal Component Analysis) and ECNN, we are able to identify instances of hate speech in the text (Enhanced Convolutional Neural Network). With the use of NLP, a fully autonomous system for assessing syntax and meaning can be established (NLP). There is a strong emphasis on pre-processing, feature extraction, and classification. Cleansing the text by removing extra spaces, punctuation, and stop words is what normalization is all about. In the process of extracting features, these features that have already been processed are used. During the feature extraction process, the MPCA algorithm is used. It takes a set of related features and pulls out the ones that tell us the most about the dataset we give itThe proposed categorization method is then put forth as a means of detecting instances of hate speech or abusive language. It is argued that ECNN is superior to other methods for identifying hateful content online. It can take in massive amounts of data and quickly return accurate results, especially for larger datasets. As a result, the proposed MPCA+ECNN algorithm improves not only the F-measure values, but also the accuracy, precision, and recall.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.49-67
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• 2015

Recently, emerging the notion of big data and social media has led us to enter data's big bang. Social networking services are widely used by people around the world, and they have become a part of major communication tools for all ages. Over the last decade, as online social networking sites become increasingly popular, companies tend to focus on advanced social media analysis for their marketing strategies. In addition to social media analysis, companies are mainly concerned about propagating of negative opinions on social networking sites such as Facebook and Twitter, as well as e-commerce sites. The effect of online word of mouth (WOM) such as product rating, product review, and product recommendations is very influential, and negative opinions have significant impact on product sales. This trend has increased researchers' attention to a natural language processing, such as a sentiment analysis. A sentiment analysis, also refers to as an opinion mining, is a process of identifying the polarity of subjective information and has been applied to various research and practical fields. However, there are obstacles lies when Korean language (Hangul) is used in a natural language processing because it is an agglutinative language with rich morphology pose problems. Therefore, there is a lack of Korean natural language processing resources such as a sentiment lexicon, and this has resulted in significant limitations for researchers and practitioners who are considering sentiment analysis. Our study builds a Korean sentiment lexicon with collective intelligence, and provides API (Application Programming Interface) service to open and share a sentiment lexicon data with the public (www.openhangul.com). For the pre-processing, we have created a Korean lexicon database with over 517,178 words and classified them into sentiment and non-sentiment words. In order to classify them, we first identified stop words which often quite likely to play a negative role in sentiment analysis and excluded them from our sentiment scoring. In general, sentiment words are nouns, adjectives, verbs, adverbs as they have sentimental expressions such as positive, neutral, and negative. On the other hands, non-sentiment words are interjection, determiner, numeral, postposition, etc. as they generally have no sentimental expressions. To build a reliable sentiment lexicon, we have adopted a concept of collective intelligence as a model for crowdsourcing. In addition, a concept of folksonomy has been implemented in the process of taxonomy to help collective intelligence. In order to make up for an inherent weakness of folksonomy, we have adopted a majority rule by building a voting system. Participants, as voters were offered three voting options to choose from positivity, negativity, and neutrality, and the voting have been conducted on one of the largest social networking sites for college students in Korea. More than 35,000 votes have been made by college students in Korea, and we keep this voting system open by maintaining the project as a perpetual study. Besides, any change in the sentiment score of words can be an important observation because it enables us to keep track of temporal changes in Korean language as a natural language. Lastly, our study offers a RESTful, JSON based API service through a web platform to make easier support for users such as researchers, companies, and developers. Finally, our study makes important contributions to both research and practice. In terms of research, our Korean sentiment lexicon plays an important role as a resource for Korean natural language processing. In terms of practice, practitioners such as managers and marketers can implement sentiment analysis effectively by using Korean sentiment lexicon we built. Moreover, our study sheds new light on the value of folksonomy by combining collective intelligence, and we also expect to give a new direction and a new start to the development of Korean natural language processing.

• Child Studies in Asia-Pacific Contexts
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• v.3 no.2
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• pp.81-103
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• 2013

This study explored social media use among 50 adolescents attending a public high school in a non-Western community. Adolescents participated in focus group interviews and completed a written self-report survey. Findings revealed that these teenagers use electronic communication forms such as phone texting and social networking sites to connect with friends and family. They show a preference for Facebook, YouTube, and Instagram, do not engage in risky Internet behavior, and acknowledge both positive and negative aspects of electronic communication forms. In addition, their selection of electronic communication forms is dependent upon several factors that include the strength of the relationship and type of discourse exchange. For example, they reserve phone texting and cell use, which are more private communication mediums for family and friends. Electronic communication did not replace face-to-face interactions; rather it complemented and extended those interactions. Findings support existing literature on adolescent social media use and those shared with other collectivist cultural groups.

• Journal of Information Processing Systems
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• v.17 no.1
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• pp.163-177
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• 2021

Many methods of discovering social networking communities or clustering of features are based on the network structure or the content network. This paper proposes a community discovery method based on topic models using a time factor and an unsupervised clustering method. Online community discovery enables organizations and businesses to thoroughly understand the trend in users' interests in their products and services. In addition, an insight into customer experience on social networks is a tremendous competitive advantage in this era of ecommerce and Internet development. The objective of this work is to find clusters (communities) such that each cluster's nodes contain topics and individuals having similarities in the attribute space. In terms of social media analytics, the method seeks communities whose members have similar features. The method is experimented with and evaluated using a Vietnamese corpus of comments and messages collected on social networks and ecommerce sites in various sectors from 2016 to 2019. The experimental results demonstrate the effectiveness of the proposed method over other methods.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.196-198
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• 2016

Online social networking sites such as MySpace, Facebook, Twitter are becoming very preeminent, and the quantities of their users are escalating very quickly. Due to the significant escalation of security vulnerabilities in social networks, user's confidentiality, authenticity, and privacy have been affected too. In this paper, a short study of online social network attacks is presented in order to identify the problems and impact of the attacks on World Wide Web (WWW).

• International Journal of Contents
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• v.15 no.4
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• pp.74-81
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• 2019

This study examined the overall relationship between information privacy concern, need for uniqueness (NFU), and disclosure behavior to explain the personal factors that drive data-sharing on Facebook. The results of an online survey conducted with 222 Facebook users show that among diverse data that social media users disclose online, four distinct factors are identified: basic personal data, private data, personal opinions, and personal photos. In general, there is a negative relationship between privacy concern and a positive relationship between the NFU and the willingness to self-disclose information. Overall, the NFU was a better predictor of willingness to disclose information than privacy concern, gender, or age. While privacy concern has been identified as an influential factor when users evaluate social networking sites, the findings of this study contribute to the literature by demonstrating that an individual's need to manifest individualization on social media overrides privacy concerns.