• Title/Summary/Keyword: twitter

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Keywords and Topic Analysis of Social Issues on Twitter Based on Text Mining and Topic Modeling (텍스트 마이닝과 토픽 모델링을 기반으로 한 트위터에 나타난 사회적 이슈의 키워드 및 주제 분석)

  • Kwak, Soo Jeong;Kim, Hyon Hee
    • KIPS Transactions on Software and Data Engineering
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    • v.8 no.1
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    • pp.13-18
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    • 2019
  • In this study, we investigate important keywords and their relationships among the keywords for social issues, and analyze topics to find subjects of the social issues. In particular, we collected twitter data with the keyword 'metoo' which has attracted much attention in these days, and perform keyword analysis and topic modeling. First, we preprocess the twitter data, identified important keywords, and analyzed the relatedness of the keywords. After then, topic modeling is performed to find subjects related to 'metoo'. Our experimental results showed that relatedness of keywords and subjects on social issues in twitter are well identified based on keyword analysis and topic modeling.

Malaria Epidemic Prediction Model by Using Twitter Data and Precipitation Volume in Nigeria

  • Nduwayezu, Maurice;Satyabrata, Aicha;Han, Suk Young;Kim, Jung Eon;Kim, Hoon;Park, Junseok;Hwang, Won-Joo
    • Journal of Korea Multimedia Society
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    • v.22 no.5
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    • pp.588-600
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    • 2019
  • Each year Malaria affects over 200 million people worldwide. Particularly, African continent is highly hit by this disease. According to many researches, this continent is ideal for Anopheles mosquitoes which transmit Malaria parasites to thrive. Rainfall volume is one of the major factor favoring the development of these Anopheles in the tropical Sub-Sahara Africa (SSA). However, the surveillance, monitoring and reporting of this epidemic is still poor and bureaucratic only. In our paper, we proposed a method to fast monitor and report Malaria instances by using Social Network Systems (SNS) and precipitation volume in Nigeria. We used Twitter search Application Programming Interface (API) to live-stream Twitter messages mentioning Malaria, preprocessed those Tweets and classified them into Malaria cases in Nigeria by using Support Vector Machine (SVM) classification algorithm and compared those Malaria cases with average precipitation volume. The comparison yielded a correlation of 0.75 between Malaria cases recorded by using Twitter and average precipitations in Nigeria. To ensure the certainty of our classification algorithm, we used an oversampling technique and eliminated the imbalance in our training Tweets.

Decomposing Twitter Network in Tourism Marketing

  • Kim, Wonsik;Kim, Daegeun
    • International Journal of Advanced Culture Technology
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    • v.9 no.2
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    • pp.80-85
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    • 2021
  • This study is to analyze the structure of the networks of tourism marketing on Twitter, identifying the most prominent users, the flow of information about tourism marketing, and the interaction between the users posting tweets. This study employs NodeXL pro as a visualization software package for social network analysis. The number of vertices or nodes is 171, and the number of the unique edges or links is 128, but there are 101 edges with duplicates, so the total links are 229, which means that there are fewer Twitter accounts in the social network on tourism marketing, but they have a few close relationships by sharing information. The research can map the social network of communicators of tourism marketing using Twitter data. The network has a complicated pattern, including one independent network and some connected networks. Some mediators connect each network and can control the information flow of tourism marketing. More communicators are getting the information than the ones providing it, which means that there is likely to be the dependence of information among communicators that can cause an obstacle and distortion of the information flow system, especially in the independent network.

Development of Restaurant Recommendation System Using K-Pop Hashtag Crawling (K-POP 연관 해시태그 크롤링을 이용한 맛집 추천 시스템 개발)

  • Kim, Hwa-Seon;Lee, Chae-Yeon;Cho, Seo-Yun;Nah, Jeong-Eun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2022.11a
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    • pp.878-880
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    • 2022
  • COVID-19 상황 속에서도 전 세계 Twitter K-POP 콘텐츠 관련 트윗 양은 78억 건 이상으로 매년 성장세를 보인다. Twitter 내 K-POP 팬들은 아티스트 관련 해시태그를 포함한 트윗을 작성하여 같은 팬덤끼리 실시간으로 정보를 전달하고 생산한다. 이러한 맛집 트윗들은 K-POP 팬들이 Twitter 내에서 신뢰도 있는 맛집 정보를 얻는 용도로 사용된다. 하지만 팬들이 정보를 얻기 위해서는 여러 맛집 해시태그로 검색하고 리트윗 수가 많은 트윗을 직접 찾아야 한다. 기존의 맛집 추천 시스템은 서비스 제공자 중심의 구조를 띤다. 서비스 제공자가 일방적으로 정보를 전달하거나, 사용자 리뷰 갱신 간격이 길다는 한계가 존재한다. 본 논문에서는 Twitter 내 K-POP 맛집 해시태그가 포함된 트윗을 Twitter API와 Tweepy를 사용하여 크롤링하였다. 수집한 데이터의 좋아요 수와 리트윗 수를 바탕으로 데이터 필터링을 진행하여 bot user와 광고 계정이 제외된 맛집 관련 트윗을 추출한다. 최종적으로는 추출한 트윗의 정보를 마커로 표시하여 웹 사이트를 제작하였다. K-POP 팬들은 맛집 해시태그를 검색하여 일일이 찾을 필요 없이 웹 사이트에 방문하여 맛집 위치를 확인할 수 있다. 웹 사이트 사용자의 위치가 지도상에 표시되어 가까운 맛집을 찾기도 편리하다. 본 논문에서는 맛집의 위치를 서대문구로 한정하여 진행했다.

Information Diffusion Difference by Product Type Based on Social Media Type (소셜 미디어 유형에 기반한 제품유형에 따른 정보 확산 차이)

  • Heon Baek
    • Information Systems Review
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    • v.19 no.3
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    • pp.91-104
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    • 2017
  • This study aims to understand the differences in the media characteristics of two types of media, namely, Blog and Twitter, as well as in their factors that affect product information diffusion. To achieve these objectives, the information diffusion pattern is identified by analyzing the number of product-related posts in each media based on the Bass model. The analysis results revealed that the information diffusion speed of hedonic goods was faster than that of utilitarian goods. Regardless of product type, Twitter had a higher imitation effect than Blog, while Blog had a higher innovation effect than Twitter. The results implied that users of Blog tended to find information by themselves while those of Twitter relied more on the others' evaluation than their own subjective evaluations of innovations.

An empirical evaluation of electronic annotation tools for Twitter data

  • Weissenbacher, Davy;O'Connor, Karen;Hiraki, Aiko T.;Kim, Jin-Dong;Gonzalez-Hernandez, Graciela
    • Genomics & Informatics
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    • v.18 no.2
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    • pp.24.1-24.7
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    • 2020
  • Despite a growing number of natural language processing shared-tasks dedicated to the use of Twitter data, there is currently no ad-hoc annotation tool for the purpose. During the 6th edition of Biomedical Linked Annotation Hackathon (BLAH), after a short review of 19 generic annotation tools, we adapted GATE and TextAE for annotating Twitter timelines. Although none of the tools reviewed allow the annotation of all information inherent of Twitter timelines, a few may be suitable provided the willingness by annotators to compromise on some functionality.

A study on finding influential twitter users by clustering and ranking techniques (클러스터링 및 랭킹 기법을 활용한 트위터 인플루엔셜 추출 연구)

  • Choi, Jun-Il;Chang, Joong-Hyuk
    • Journal of Korea Society of Industrial Information Systems
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    • v.20 no.1
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    • pp.19-26
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    • 2015
  • Recently, a lot of users are using social network services as the spread of SNS and generalization of smart-phone. In this study, we apply clustering and ranking method for finding twitter influential users. First, we propose five ranking elements. The five elements include the number of follow, the number of retweet, IRP, IFP and influ-score. These elements are used by centroid point of clustering methods. This study can help to find novel approaches for finding twitter influential users.

Classifying Temporal Topics with Similar Patterns on Twitter

  • Yun, Hong-Won
    • Journal of information and communication convergence engineering
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    • v.9 no.3
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    • pp.295-300
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    • 2011
  • Twitter is a popular microblogging service that enables the users to send and read short text messages. These messages are becoming source to analyze topic trends and identify relations among temporal topics. In this paper, we propose a method to classify the temporal topics on Twitter as a problem of grouping the similar patterns. To provide a starting point for a classification under the same topics, we identify the content word weighting scheme based on Latent Dirichlet Allocation (LDA). And we formulate how the temporal topics in the time window can be classified like peaky topics, constant topics, and periodic topics. We provide different real case studies which show the validity of the proposed method. Evaluations show that the proposed method is useful as a classifying model in the analysis of the temporal topics.

Interacting or Just Acting? -A Case Study of European, Korean, and American Politicians' Interactions with the Public on Twitter

  • Otterbacher, Jahna;Shapiro, Matthew A.;Hemphill, Libby
    • Journal of Contemporary Eastern Asia
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    • v.12 no.1
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    • pp.5-20
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    • 2013
  • Social media holds the potential to facilitate vertical political communication by giving citizens the opportunity to interact directly with their representatives. However, skeptics claim that even when politicians use "interactive media," they avoid direct engagement with constituents, using technology to present a façade of interactivity instead of a genuine dialogue. This study explores how elected officials in three regions of the world are using Twitter to interact with the public. Using the Twitter activity of 15 officials over a period of six months, we show that in addition to the structural features of Twitter that are designed to promote interaction, officials rely on language to foster or to avoid engagement. We also provide evidence that the existence of interactive features does not guarantee interactivity.

The Effects of Hispanics' Social TV Participation on Ethnic Identifications

  • Natascha Ginelia, Perez-Rios;Eunice (Eun-Sil), Kim
    • 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.