• 제목/요약/키워드: online social networking

검색결과 143건 처리시간 0.023초

Why Social Comparison on Instagram Matters: Its impact on Depression

  • Hwnag, Ha Sung
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권3호
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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.

소셜 데이터를 위한 효율적인 데이터 처리 기법 (Efficient Data Processing Method for Social Data)

  • 김성림;권준희
    • 디지털산업정보학회논문지
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    • 제9권3호
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    • pp.31-38
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    • 2013
  • The evolution of the Web from Web 1.0 to Web 2.0 has brought up new platforms as SNSs(Social Network Service) that are used by users to articulate and manage their relationships. SNSs are an online phenomenon which has become extremely popular. A SNS essentially consists of a representation of each user, his/her social links, and a variety of additional services. SNSs are increasingly attracting the attention of academic and industry researchers. What makes SNS unique is that they have a relationship with friends. The friend recommendation is one important feature of social networking services. People tend to trust the opinions of friends they know rather than the opinions of strangers. In this paper, we propose an efficient data processing method for social data. We study previous researches about social score in social network service. Our ESS(Efficient Social Score) is computed by both friendship weight and score of a document that was tagged by a user's friends. Our experimental results also confirm that our method has good performance.

Competitive intelligence in Korean Ramen Market using Text Mining and Sentiment Analysis

  • Kim, Yoosin;Jeong, Seung Ryul
    • 인터넷정보학회논문지
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    • 제19권1호
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    • pp.155-166
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    • 2018
  • These days, online media, such as blogospheres, online communities, and social networking sites, provides the uncountable user-generated content (UGC) to discover market intelligence and business insight with. The business has been interested in consumers, and constantly requires the approach to identify consumers' opinions and competitive advantage in the competing market. Analyzing consumers' opinion about oneself and rivals can help decision makers to gain in-depth and fine-grained understanding on the human and social behavioral dynamics underlying the competition. In order to accomplish the comparison study for rival products and companies, we attempted to do competitive analysis using text mining with online UGC for two popular and competing ramens, a market leader and a market follower, in the Korean instant noodle market. Furthermore, to overcome the lack of the Korean sentiment lexicon, we developed the domain specific sentiment dictionary of Korean texts. We gathered 19,386 pieces of blogs and forum messages, developed the Korean sentiment dictionary, and defined the taxonomy for categorization. In the context of our study, we employed sentiment analysis to present consumers' opinion and statistical analysis to demonstrate the differences between the competitors. Our results show that the sentiment portrayed by the text mining clearly differentiate the two rival noodles and convincingly confirm that one is a market leader and the other is a follower. In this regard, we expect this comparison can help business decision makers to understand rich in-depth competitive intelligence hidden in the social media.

Online Tie Formation in Enterprise Social Media

  • Yongsuk Kim;Gerald C. (Jerry) Kane
    • Asia pacific journal of information systems
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    • 제29권3호
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    • pp.382-406
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    • 2019
  • We study the antecedents to tie formation on an (Facebook-like) enterprise social media platform implemented to support cross-boundary connections. Research has produced mixed findings regarding the role of social media in cultivating bridging vs. closed networks. We examine the tie formation patterns of 1,386 enterprise social media users over a two-year period. Specifically, we observe who became (or chose not s become) "friends" with whom at the dyadic level and relate the decisions to various mechanisms that affect one's network to expand, constrain, or bridge. Using logistic and OLS regressions, we find that users tend to form ties via reciprocity and transitivity (with friends of friends), both of which help expand one's network. We also find strong networking tendency toward functional and hierarchical homophily (same business unit and same rank, respectively), which is likely to constrain one's network (closed network structure). We find that one's participation in various online interest groups is likely to open one's network (bridging network structure) while no evidence found for preferential attachment. Overall, we find that enterprise social media offers features, some of which are likely to foster bridging while others foster closed networks via different mechanisms.

Online Collaborative Language Learning for Enhancing Learner Motivation and Classroom Engagement

  • Jeong, Kyeong-Ouk
    • International Journal of Contents
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    • 제15권4호
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    • pp.89-96
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    • 2019
  • This study examines the impact of online collaborative English language learning to enhance learner motivation and classroom engagement in university English instruction. The role of learner motivation and classroom engagement has gained much attention under the premises of current constructivist framework of English as a foreign language education. To promote learner motivation and classroom interaction in English instruction, participants in this study engaged in integrative English learning activities through online group collaboration and peer-tutoring. They exchanged productive peer response and shared their learning experiences throughout the integrative English learning activities. Digital technology played an integral role in motivating the learning process of the participants. Data for this study were gathered through an online questionnaire survey and semi-structured interviews. The data were analyzed based on the ARCS motivational model of instructional design to identify the motivational aspects of integrative English learning activities. This study reveals that participants of this study regarded online collaborative English learning activities as the positive and motivating learning experience. The online collaborative English reading instruction had positive effect on improving EFL university students' learning performance. Participants of this study also identified affective and metacognitive benefits of online collaborative EFL learning activities for learner motivation and classroom engagement. This study reveals that the social networking platform in online group collaboration played a crucial role for the participants in understanding the integration of online group collaboration as the positive and effective language learning strategy. This study may have implications in suggesting the effective instructional design for promoting learner motivation and classroom interaction in EFL education.

페이스북 인사이트 데이터 분석 (Data Analysis of Facebook Insights)

  • 차영준;이학준;정용규
    • 문화기술의 융합
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    • 제2권1호
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    • pp.93-98
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    • 2016
  • 최근 정보통신기술의 발달로 인한 각종 모바일 기기와 스마트 기기를 통해 소셜 네트워크 서비스가 많이 대중화 되고 있다. SNS는 오프라인에 존재하는 사회적 관계망이 온라인으로 이동한 친목기반 인맥 형성 서비스이다. SNS는 온라인 커뮤니티와 혼동되어 사용되기도 하지만 차이점이 있다. 이러한 기기들로부터 수집된 정보를 모델링하는 알고리즘으로는 연관성, 군집화, 신경망, 결정 나무 등의 다양한 기법이 제안되고 있다. 이러한 기법들을 활용하여 여러 가지 방대한 자료를 효과적으로 사용 하는데 연구할 필요가 있다. 따라서 본 논문에서는 특히 군집화에서 좋은 성능으로 평가받는 EM 알고리즘에 대해서 페이스북 인사이트 데이터를 이용하여 군집화를 수행한 결과를 기반으로 알고리즘의 성능을 평가하였다. 이를 통하여 EM알고리즘에 따른 성능의 변화와 남호주 주립도서관 의 실험데이터의 적용결과를 기반으로 분석하였다.

Storytelling and Social Networking: Why Luxury Brand Needs to Tell Its Story

  • Park, Min-Sook
    • Journal of Information Technology Applications and Management
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    • 제27권5호
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    • pp.69-80
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    • 2020
  • Recently, luxury brands are selling their products to consumers using their own direct online channels. In the online channel, marketing strategy through storytelling is needed because consumers do not have enough product experience. Therefore, luxury brands are actively utilizing social media and delivering stories includes their birth and growth. Unlike mass media, social media communicates with consumers more quickly and frequently and delivers the story of brand naturally. This study classifies luxury brands into four groups based on story recognition of luxury brands and self-esteem, and analyzes and materializes each group of the propensities of luxury brand consumption. It also tries to draw strategic implications for effective SNS advertising by analyzing narrative transportation on SNS advertising, interests in videos, and the interests in story based on these typified groups of luxury consumption. The result of the analysis shows that there is a difference in consumption propensity among consumers who were classified into four groups according to story cognition of luxury brands and self-esteem. There is also a difference in the response to narrative images through SNSs, such as narrative transportation, interests in videos, and interests in brand stories.

이종 소셜 네트워크 상에서 친구계정의 이름을 이용한 사용자 식별 기법 (Exploiting Friend's Username to De-anonymize Users across Heterogeneous Social Networking Sites)

  • 김동규;박석
    • 정보과학회 논문지
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    • 제41권12호
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    • pp.1110-1116
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    • 2014
  • 온라인 소셜 네트워크 서비스(online social network service)를 사용하는 사용자의 증가와 더불어 Twitter, LinkedIn, Tumblr 등 다양한 주제의 SNS들이 등장하고 있다. 사용자들은 SNS에 자신의 정보를 자발적으로 제공하고 서비스를 사용하나, 대용량 데이터 처리 기술의 발전과 프라이버시에 대한 인식이 고취됨에 따라 SNS 이용에 따른 프라이버시 침해가 문제점으로 부각되고 있다. 이를 해결하기 위해 기계 학습에 기반을 둔 SNS 상의 프라이버시 보호 기법들이 연구되어왔으며, 지금도 활발히 연구가 진행중이나 새로운 SNS의 등장에 따른 프라이버시 침해 사례들이 지속적으로 제기되고 있다. 본 논문은 SNS에서 써드 파티 애플리케이션 개발자, 혹은 서비스 제공자가 악의를 가지고 SNS 사용자의 프라이버시를 침해하는 상황에서 사용자가 프라이버시 유출을 사전 탐지하는 기법을 제안한다.

Information Behavior on Social Live Streaming Services

  • Scheibe, Katrin;Fietkiewicz, Kaja J.;Stock, Wolfgang G.
    • Journal of Information Science Theory and Practice
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    • 제4권2호
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    • pp.6-20
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    • 2016
  • In the last few years, a new type of synchronous social networking services (SNSs) has emerged—social live streaming services (SLSSs). Studying SLSSs is a new and exciting research field in information science. What information behaviors do users of live streaming platforms exhibit? In our empirical study we analyzed information production behavior (i.e., broadcasting) as well as information reception behavior (watching streams and commenting on them). We conducted two quantitative investigations, namely an online survey with YouNow users (N = 123) and observations of live streams on YouNow (N = 434). YouNow is a service with video streams mostly made by adolescents for adolescents. YouNow users like to watch streams, to chat while watching, and to reward performers by using emoticons. While broadcasting, there is no anonymity (as in nearly all other WWW services). Synchronous SNSs remind us of the film The Truman Show, as anyone has the chance to consciously broadcast his or her own life real-time.

Discovering Community Interests Approach to Topic Model with Time Factor and Clustering Methods

  • Ho, Thanh;Thanh, Tran Duy
    • Journal of Information Processing Systems
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    • 제17권1호
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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.