scholarly journals Social Network Analysis: #BlackLivesMatter Distribution at Actor Level and System Level

2021 ◽  
Vol 6 (2) ◽  
pp. 275-283
Author(s):  
Edy Prihantoro ◽  
Rizky Wulan Ramadhani
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Quantitative Methods ◽  
Closeness Centrality ◽  
System Level ◽  
Eigenvector Centrality ◽  
Black Lives Matter ◽  
A Value ◽  
Twitter Users

#BlackLivesMatter accompanies several cases of discrimination against the black community. The hashtag was spread by actors who have great influences on Twitter users. The actors create communication network which connected to each other to form opinions about the Black Lives Matter movement. Researchers conducted a study to determine the distribution of #BlackLivesMatter at the actor level for the period 20-27 April 2021 in Twitter. The study used quantitative methods and a positivistic paradigm with a Social Network Analysis (SNA) approach. The results show that the actor with the highest degree of centrality is @jeanmessiha with 238 interactions, the actor with the highest betweenness centrality is @helloagain0611 with a value of 0.000049, the actor with the highest eigenvector centrality is @jeanmessiha with a value of 1 and there are 1,416 actors who have closeness centrality. # BlackLivesMatter has a low diameter value so that it spreads quickly but not too widely, not much reciprocity occurs, not concentrated in one dominant cluster but spread widely in several clusters. The actors play a role in spreading diverse opinions regarding Black Lives Matter, thus creating free discussion in several clusters on Twitter. Opinion widely spread on Twitter creates public opinion regarding the Black Lives Matter movement.

scholarly journals Peran Pers Sebagai Aktor Gerakan Digital Tagar #SolidaritasUntukNTT di Twitter

2021 ◽  
Vol 5 (1) ◽  
pp. 98
Author(s):  
Gema Nusantara Bakry ◽  
Ika Merdekawati Kusmayadi
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Betweenness Centrality ◽  
Closeness Centrality ◽  
Degree Centrality ◽  
Eigenvector Centrality ◽  
Personal Network

Peristiwa banjir bandang yang diakibatkan Siklon Seroja telah mengundang perhatian dan simpati masyarakat Indonesia. Berbagai upaya telah dilakukan untuk berkontribusi dalam upaya penanggulangan dampak yang diterima oleh masyarakat NTT. Salah satu upaya yang dilakukan oleh masyarakat adalah mengampanyekan gerakan sosial digital #SolidaritasUntukNTT di Twitter. Gerakan sosial digital melalui pesan-pesan tertentu dapat menggugah kesadaran bagi penggunanya. Untuk mengetahui efektivitas penyebaran pesan dalam gerakan sosial digital dapat divisualisasikan menggunakan metode Social Network Analysis (SNA).  Penelitian ini bertujuan untuk memvisualisasikan peran pers dalam mendistribusikan pesan gerakan sosial digital dengan tagar #SolidaritasUntukNTT. Metode penelitian yang digunakan adalah analisis jaringan sosial dengan teori graf di Twitter. Hasil analisis dan visualisasi jaringan dilakukan di aplikasi Gephi dengan algoritma Yifan Hu untuk melihat distribusi pola pesan dan peran pers pada tagar #SolidaritasUntukNTT. Penelitian ini menggambarkan tipe jaringan two mode yang terdiri dari interaksi antara individu dan organisasi dengan pola komunikasi radial personal network yang memiliki ciri jaringan terbuka dan kohesivitas yang rendah dengan arah relasi directed dan asimetris. Analisis peran pers diukur melalui sentralitas aktor untuk mengetahui degree centrality, closeness centrality, betweenness centrality dan eigenvector centrality. Aktor @vice_id diketahui sebagai aktor yang memiliki degree dan eigenvector centrality tertinggi dibandingkan dengan aktor pers lainnya. Aktor @idntimes dan @detikcom memiliki nilai closeness dan betweenness centrality yang lebih tinggi dari media lainnya. Analisis jaringan sosial memberikan pemahaman terkait distribusi pesan dalam media sosial untuk mengetahui efektivitas pesan yang didistribusikan oleh beberapa aktor jaringan, khususnya peran pers dalam mengampanyekan gerakan sosial di media. Oleh karena itu, metode SNA dapat digunakan untuk penelitian jurnalisme data. 

scholarly journals POLA INTERAKSI DAN AKTOR YANG PALING BERPERAN PADA EVENT JGTC 2013 MELALUI MEDIA SOSIAL TWITTER (STUDI MENGGUNAKAN METODE SOCIAL NETWORK ANALYSIS)

2017 ◽  
Vol 14 (3) ◽  
pp. 201 ◽  
Author(s):  
Rio Oktora ◽  
Andry Alamsyah
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Closeness Centrality ◽  
Degree Centrality ◽  
Eigenvector Centrality ◽  
Analysis Software ◽  
Social Media Monitoring ◽  
Media Monitoring ◽  
Programming Interface

Selama beberapa tahun terakhir, internet telah berkembang dengan cepat seiring dengan perkembangan teknologi. Data percakapan yang terdapat di media sosial dapat dimanfaatkan untuk melihat pola interaksi dan aktor yang paling berperan pada event JGTC 2013 melalui media sosial Twitter. Penelitian ini memanfaatkan big data dari media sosial Twitter yang diperoleh dari Twitter melalui API (Aplication Programming Interface) dengan bantuan teknis dari NoLimitID (perusahaan social media monitoring & analytic tools). Data tersebut kemudian diolah dengan pendekatan Social Network Analysis. Software yang digunakan untuk menghitung dan menvisualisasikan hasil analysis adalah Gephi. Penentuan aktor yang berperan dalam event JGTC 2013 dihitung berdasarkan centrality yang terdiri dari degree centrality, betweenness centrality, closeness centrality, dan eigenvector centrality. Sampel dalam penelitian ini adalah tweet yang berupa interaksi (terdapat mention, baik berupa reply maupun qoute retweet) yang memuat kata 'JGTC' dan '#JGTC36' pada 1 Desember 2013. Hasil penelitian pada event JGTC 2013 terdapat 7624 node (akun) yang terlibat dengan 7445 edge (interaksi) yang terjadi di network tersebut. Aktor (node) yang paling berpengaruh dalam network JGTC secara keseluruhan adalah raisa6690 yang merupakan bintang tamu pengisi acara event JGTC 2013

scholarly journals A network analysis of character relations in Etienne van Heerden’s Toorberg

Literator ◽  
2013 ◽  
Vol 34 (2) ◽  
Author(s):  
Burgert A. Senekal
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Betweenness Centrality ◽  
Theoretical Framework ◽  
Closeness Centrality ◽  
Degree Centrality ◽  
Eigenvector Centrality ◽  
Traditional Concept ◽  
Family Ties

Etienne van Heerden’s Toorberg can be approached as a modern, postcolonial farm novel, partly because it challenges the concept of lineage of inheritance, which is characteristic of the traditional farm novel. Lineage of inheritance implies a strong family bond, and it is therefore instructive to investigate how family ties function within this novel. The article views family ties within Toorberg using Social Network Analysis (SNA), a largely unknown theoretical framework that can also be applied within the study of literature. It is shown how characters’ positions in this network can be calculated in terms of degree centrality, closeness centrality, Eigenvector centrality and betweenness centrality, and how these measures expose the way in which this novel undermines the traditional concept of inheritance.

scholarly journals The Social Engagement to Agricultural Issues using Social Network Analysis

2021 ◽  
Vol 10 (1) ◽  
pp. 1-7
Author(s):  
Tanty Yanuar Widiyanti ◽  
Teguh Bharata Adji ◽  
Indriana Hidayah
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Engagement ◽  
Betweenness Centrality ◽  
Closeness Centrality ◽  
Degree Centrality ◽  
Eigenvector Centrality ◽  
The Government

Twitter is one of the micro-blogging social media which emphasizes the speed of communication. In the 4.0 era, the government also promotes the distribution of information through social media to reach the community from various lines.  In previous research, Social Network Analysis was used to see the relationship between actors in a work environment, or as a basis for identifying the application of technology adoption in decision making, whereas no one has used SNA to see trends in people's response to agricultural information. This study aims to see the extent to which information about agriculture reaches the community, as well as to see the community's response to take part in agricultural development.  This article also shows the actors who took part in disseminating information. Data was taken on November 13 to 20, 2020 from the Drone Emprit Academic, and was taken limited to 3000 nodes. Then, the measurements of the SNA are represented on the values of Degree Centrality, Betweenness Centrality, Closeness Centrality, and Eigenvector Centrality. @AdrianiLaksmi has the highest value in Eigenvector Centrality and Degree Centrality, he has the greatest role in disseminating information and has many followers among other accounts that spread the same information. While the @RamliRizal account ranks the highest in Betweenness Centrality, who has the most frequently referred information, and the highest Closeness Centrality is owned by the @baigmac account because of the fastest to re-tweet the first information.

scholarly journals A study on the influence of Korean Middle School students' relationship through Science class applying STAD cooperative learning

2018 ◽  
Vol 8 (4) ◽  
pp. 291 ◽  
Author(s):  
Dongryeul Kim
Keyword(s):  
Middle School ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Middle School Students ◽  
Collaborative Learning ◽  
Closeness Centrality ◽  
Degree Centrality ◽  
Science Class ◽  
School Students

  In order to find out the influence of Korean Middle School Students' relationship by science class applying STAD collaborative learning, this study conducted a social network analysis and sought to analyze the communication networks within the group and identified the change process of the type. The subject of this study was 30 students of the second grade at the girls' middle school located in Korea's Metropolitan City. For five weeks, science class applying STAD Collaborative Learning was implemented in the ‘reproduction and generation’ chapter. First, the class social network analysis showed that all the prices of density, degree centrality, closeness centrality, and betweenness centrality have risen after science class applying STAD Collaborative Learning. Also, the classroom's relationship index has improved. In other words, STAD Collaborative Learning encouraged interaction among students. Second, in order to research popularity, students' centrality analysis through the class social network analysis showed that top-ranked students' values of density, degree centrality, closeness centrality, and betweenness centrality appeared commonly high after science class applying STAD Collaborative Learning. Third, the analysis of the communication network change within six groups showed that all channel type appeared most often and circle type also appeared anew after science class applying STAD Collaborative Learning. In other words, it was possible to exchange information freely and communicate with all members of the group through STAD Collaborative Learning.

scholarly journals PEMETAAN PERILAKU BERISIKO GAY BERBASIS SNA SEBAGAI EARLY WARNING SYSTEM KASUS HIV/AIDS DI KOTA KENDARI

2019 ◽  
Vol 4 (1) ◽  
Author(s):  
Jumartin Gerung
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Closeness Centrality ◽  
Degree Centrality ◽  
Betweeness Centrality ◽  
Hiv Aids

AbstrakPada kasus HIV dalam skala nasional, menunjukkan bahwa kelompok heteroseks juga termasuk sebagai kelompokutama yang paling berisiko menderita HIV/AIDS. Peningkatan ini mencolok terijadi sejak 2015 angkanya masih di 4.241 kasus, dan meningkat hingga lebih dari dua kali lipat pada 2016 yang mencapai 13.063 kasus. Data pemetaaninteraksi di sosial media khususnya wilayah Kendari terdapat sekitar 800 akun yang memberi interaksi perihal Gay.Hal ini diindikasikan akan mempengaruhi prevalensi kejadian HIV/AIDS di Kota Kendari. Penelitian ini bertujuan untukmemetakan interaksi perilaku berisiko Gay sebagai early warning system kasus HIV/AIDS. Social Network Analysismerupakan studi yang mempelajari tentang hubungan manusia dengan memanfaatkan teori graf. Penerapan SocialNetworkAnalysis dalam suatu aplikasi mampu menggambarkan relasi atau hubungan antar individu denganmelakukan visualisasi terkait centrality (titik pusat), between centrality (jalur pendek), juga closeness centrality yaknirata-rata jalur terpendek dari interaksi akun di laman FB. Untuk platform Facebook berdasarkan pada hasilpenghitungan diketahui bahwa akun yang berpengaruh terhadap interaksi jejaring sosial adalah akun Gay Kendariyang unggul pada nilai degree centrality,betweeness centrality, dan Closeness centrality. Akun Gay Kendari palingberpengaruh dalam interaksi jaringan sosial Facebook. Melalui social network analysis, penelitian ini memberikangambaran relasi perilaku berisiko LSL/Gay sebagai early warning system kasus HIV/AIDS di kota kendariKata kunci: analisis jaringan sosiai, gay, sistem peringatan dini, HIV/AIDS 

Six Degrees of Information: Using Social Network Analysis to Explore the Spread of Information Within Sport Social Networks

2012 ◽  
Vol 5 (1) ◽  
pp. 16-34 ◽  
Author(s):  
Marion E. Hambrick
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Online Social Network ◽  
Home Pages ◽  
Sporting Event ◽  
Sport Industry ◽  
Twitter Users ◽  
Promotional Messages ◽  
Share Information

Sport industry groups including athletes, teams, and leagues use Twitter to share information about and promote their products. The purpose of this study was to explore how sporting event organizers and influential Twitter users spread information through the online social network. The study examined two bicycle race organizers using Twitter to promote their events. Using social network analysis, the study categorized Twitter messages posted by the race organizers, identified their Twitter followers and shared relationships within Twitter, and mapped the spread of information through these relationships. The results revealed that the race organizers used their Twitter home pages and informational and promotional messages to attract followers. Popular Twitter users followed the race organizers early, typically within the first 4 days of each homepage’s creation, and they helped spread information to their respective followers. Sporting event organizers can leverage Twitter and influential users to share information about and promote their events.

scholarly journals Using Network Models to Analyze Old Chinese Rhyme Data (用網絡模型來分析古代漢語的韻母數據)

2016 ◽  
Vol 9 (2) ◽  
pp. 218-241 ◽  
Author(s):  
Johann-Mattis List (游函)
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Strong Evidence ◽  
Crucial Role ◽  
Quantitative Methods ◽  
Network Models ◽  
Online Application ◽  
Historical Phonology ◽  
Old Chinese

The evidence one can draw from the rhyming behavior of Old Chinese words plays a crucial role for the reconstruction of Old Chinese, and is particularly relevant to recent proposals. Some of these proposals are no longer solely based on the intuition of scholars but also substantiated by statistical arguments that help to assess the probability by which a given set of rhyming instances can be assigned to an established rhyme group. So far, however, quantitative methods were only used to confirm given hypotheses regarding rhyme groups in Old Chinese, and no exploratory analyses that would create hypotheses regarding rhyme groups in a corpus were carried out. This paper presents a new method that models rhyme data as weighted undirected networks. By representing rhyme words as nodes in a network and the frequency of rhymes in a given corpus as links between nodes, rhyme groups can be inferred with help of standard algorithms originally designed for social network analysis. This is illustrated through the construction of a rhyme network from the Book of Odes and comparing the automatically inferred rhyme groups with rhyme groups proposed in the literature. Apart from revealing interesting general properties of rhyme networks in Chinese historical phonology, the analysis provides strong evidence for a coda *-r in Old Chinese. The results of the analysis and the rhyme network of the Book of Odes can be inspected in form of an interactive online application or directly downloaded. 古代漢語的詞語所反映的韻為對上古音系的構擬，特別是對於最近的一些上古漢語構擬系統，異常重要。其中有一些構擬系統不再僅僅靠於學者的直覺，而且還用統計參數證實來評估分韻和派韻的概率。然而，迄今為止，定量方法僅用於確認關於上古韻部的假設，並且沒有進行探索性數據分析來創建初步分韻假設。本文提出了一種將韻母數據模型為加權無向網絡的新方法。此方法將韻母模型為網絡中的頂點，將某個語料庫的合韻率模型為聯頂點的邊緣，用社會網絡分析的標準算法來推斷語料庫所反映的韻母。為了更具體的說明此方法，本文用“詩經”來構建韻母網絡，而且比較自動與學者所推斷的上古韻部。除了揭示古代漢語韻網的一些有趣特點，“詩經”韻網分析了支持上古漢語韻尾* -r的新證據。“詩經”韻網和韻網分析的結果可以用交際在線應用來訪問而下載。(This article is in English.)

How users tweet about a cyber attack: An explorative study using machine learning and social network analysis

2020 ◽  
Vol 11 (2) ◽  
pp. 195-214 ◽  
Author(s):  
Daniel Vogler ◽  
Florian Meissner
Keyword(s):  
Machine Learning ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Supervised Machine Learning ◽  
Support Vector ◽  
Cyber Attack ◽  
Ticket Sales ◽  
Security Issues ◽  
Twitter Users

Cybercrime is a growing threat for firms and customers that emerged with the digitization of business. However, research shows that even though people claim that they are concerned about their privacy online, they do not act correspondingly. This study investigates how prevalent security issues are during a cyber attack among Twitter users. The case under examination is the security breach at the US ticket sales company, Ticketfly, that compromised the information of 26 million users. Tweets related to cybersecurity are detected through the application of automated text classification based on supervised machine learning with support vector machines. Subsequently, the users that wrote security-related tweets are grouped into communities through a social network analysis. The results of this multi-method study show that users concerned about security issues are mostly part of expert communities with already superior knowledge about cybersecurity.

scholarly journals Inter-player variability in game patterns in high-level women's volleyball: A study with Outside Hitters (Near vs. Away) using Social Network Analysis. [Variabilidad entre jugadores en los patrones de juego en el voleibol femenino de alto nivel: Un estudio con bateadores externos (Cerca versus Lejos) usando Análisis de Redes Sociales].

2021 ◽  
Vol 17 (65) ◽  
pp. 234-250
Author(s):  
João Bernardo Martins ◽  
◽  
Isabel Mesquita ◽  
Ademilson Mendes ◽  
Letícia Santos ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Team Sports ◽  
Eigenvector Centrality ◽  
Redes Sociales ◽  
Functional Roles ◽  
High Level ◽  
Women's Volleyball ◽  
After Error

A wide body of research on team sports has focused on positional status based differences, providing information on inter-player variability according to the functional roles within the game. However, research addressing inter-player variability within the same positional/function status is scarce. The present article presents an analysis of inter-player variability within the same positional status during critical moments, in high-level women's volleyball, using Social Network Analysis. Attack actions of the outside hitters near (OHN) and away (OHA) from the setter were analysed in ten matches from the 2019 Volleyball Nations League Finals (268 plays). Two independent Eigenvector Centrality networks were created, one for OHN and another for OHA. Main results: (a) in side-out with ideal setting conditions, the OHA used more tips and exploration of the block than the OHN; under non-ideal setting conditions, the OHN had slower attack tempos than the OHA; (b) OHA used tip and directed attacks after error situations while OHN was typically not requested after error situations; (c) in transition, OHN typically attacked after having performed a previous action, performing a dual task within each ball possession, while OHA only attacked when there was no prior action; (d) there were also inter-positional similarities, with both OHN and OHA preferring a strong attack in ideal conditions during KI and KIV, and slower tempos in transition in non-ideal conditions. Conclusions: Even within the same positional status, there seems to be subtle, but relevant inter-player variability. Consequently, coaches should devote careful attention when assigning players to positional.

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