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 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 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 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 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 

Analisis Node dengan Centrality dan Follower Rank pada Twitter

2020 ◽  
Vol 4 (5) ◽  
pp. 937-942
Author(s):  
Evangs Mailoa
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Presidential Elections ◽  
Closeness Centrality ◽  
Analysis Approach ◽  
Degree Centrality ◽  
Negative Campaigns

Twitter is used to express about something that happened. In Indonesia since 2012, Twitter has been widely used for campaigns during regional or presidential elections. Apart from positive campaigns, negative campaigns and even black campaigns were carried out via Twitter, and tweets become twitwar. Twitter is a social network, so the data can be analyzed using a social network analysis approach. This research was conducted to analyze which nodes (actors) are influential using the degree, between, and closeness centrality methods, while the follower rank method is used for the analysis of popular actors in "# 4niesKingOfDrama". The data were 8895 nodes with 23257 edges taken from January 1 to February 20, 2020. The results showed that Degree Centrality was 212 with the actor who had the highest influence score was the account @ Bangsul__88 and actor @airin_nz was the actor with the highest popularity value with Follower Rank of 0.98211783. This study found that among the 10 main actors with the highest Degree Centrality values, there were several accounts that were buzzer accounts. The node (Actor) with the highest influence value is not necessarily the node with the highest popularity value.

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 Penerapan Social Network Analysis dalam Penentuan Centrality Studi Kasus Social Network Twitter

2012 ◽  
Vol 8 (1) ◽  
Author(s):  
Budi Susanto ◽  
Herlina Lina ◽  
Antonius Rachmat Chrismanto
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Betweenness Centrality ◽  
Closeness Centrality ◽  
Specific Form ◽  
Analysis Method ◽  
System User

The twitter provides a kind of relation between users in specific form. When someone follow others, it doesn’t mean that she/he know well about them. We have defined a friend relationship between users in twitter as connection following and follower between two users. Based on this definition we develop a system to get friends and also friends of friends relation from a specific user. We use twitter API to get following and follower list and then construct a graph that represent a social network between those users. From this graph, we analyse the centrality using SNA (Social Network Analysis) method, i.e. closeness and betweeness. We propose to use these methods in order to find out who is the most influence user in the his/her social network to spread out the tweet or information. With this system, user can know about their social network based on their friend list on twitter.   Kata Kunci : Social Network Analysis, Betweenness Centrality, Closeness Centrality

scholarly journals ANALISIS JARINGAN TRANSFER PEMAIN BOLA MENGGUNAKAN METODE SOCIAL NETWORK ANALYSIS (STUDI KASUS : LIGA SPANYOL (LA LIGA) TAHUN 2015 – 2020)

2020 ◽  
Vol 17 (1) ◽  
pp. 88-95
Author(s):  
Ni Made Distiara Landephy Aryashila ◽  
Silvyana Nur Haliza ◽  
Naufal Farras Maulana ◽  
Doni Achmad Heniawan ◽  
Yudianto Yudianto
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Basic Concept ◽  
Closeness Centrality ◽  
Degree Centrality ◽  
Improve Performance ◽  
The Social ◽  
The World ◽  
Key Players

Football is a popular sport that is loved by a lot of society in the world, ranging from children to adult is very enthusiastic when discussing about soccer. The process of buying and transferring players is one element that can’t be separated in football, this process is done to improve performance and replace players who move to other clubs. Spanish league or known as La Liga is one of the major league that often transfers player, information regarding player transfers and the club itself can be seen in each season on the website transfermarkt.com. In this study we chose the Spanish League as an object of research, we use the Social Network Analysis Basic Concept technique to determine the key players of each club and players in the Spanish League in the 2015-2020 period by analyzing degree centrality, closeness centrality, dan betweenness centrality. the results of this study were displayed  Sevilla FC as a club key player, and Juanfran as a key player player

scholarly journals Social Network Analysis of Cattle Movement in Sukhothai Province, Thailand: A Study to Improve Control Measurements

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Supot Noopataya ◽  
Sukanya Thongratsakul ◽  
Chaithep Poolkhet
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Closeness Centrality ◽  
Degree Centrality ◽  
Snowball Sampling ◽  
Cattle Movement ◽  
Validated Questionnaire ◽  
One Step ◽  
Cutpoint Analysis

The aim of this study is to analyse the pattern of cattle movement in Sukhothai province, Thailand. A validated questionnaire was applied to 308 respondents related to cattle farming using one-step snowball sampling. The results showed that most of the nodes are farmers who move their animals in the province. The average normalized degree centrality and normalized closeness centrality were low (<0.01 and 0.04, resp.). We found that traders are the nodes with a high value of centrality. This corresponds with the cutpoint analysis results that traders are outstanding. In conclusion, the relevant authorities should focus on the nodes such as traders for controlling disease. However, a measure to detect disease in the early stages needs to be implemented.

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