scholarly journals Collaboration Analysis of Semarang City Dengue Hemorrhagic Fever Health Surveillance Officer with Social Network Analysis

2020 ◽  
Vol 4 (1) ◽  
pp. 1-21
Author(s):  
Lukman Santoso ◽  
Danny Manongga ◽  
Ade Iriani
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Communication Networks ◽  
Hemorrhagic Fever ◽  
Health Surveillance ◽  
Ego Networks ◽  
Network Collaboration ◽  
Flow Of Information ◽  
The City

This study aims to determine the pattern of a network collaboration between dengue hemorrhagic health surveillance personnel in the city of Semarang and to understand the flow of information deeply. The method of social network analysis / SNA (Social Network Analysis) on formal and informal communication networks between surveillance officers aims to produce sociometry and sociogram data so that the centrality of each actor in the network can be known. Interaction between Officers will be known through the analysis of the centrality of levels (degree), closeness (closeness), and intercession (betweenness). The approach used is descriptive quantitative. Data was collected using a research instrument in the form of a questionnaire, while the process of input and data analysis was carried out by looking at intact networks and ego networks carried out using UCINET. The results of the analysis show that officers dominate the centrality of the level and the intermediary with the position of Coordinator both City and District (Id. # 128, # 1, # 2, # 3). Collaboration based on working areas has a strong bond because 71% of the districts have a network density above 50%. While the value of closeness is dominated by surveillance members with id # 54, # 15, # 2, # 214, # 15 and # 10.

scholarly journals Pemanfaatan Social Network Analysis (SNA) Untuk Menganalisis Kolaborasi Panitia Pengawas Pilkada Tahun 2020 di Kecamatan Gunungpati Kota Semarang

2021 ◽  
Vol 14 (2) ◽  
pp. 244-255
Author(s):  
Lukman Santoso ◽  
Reni Veliyanti
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
High Category ◽  
Committee Network ◽  
Flow Of Information

The implementation of the 2020 Pilkada in Gunungpati District as a whole has improved in terms of the quality of its implementation. This is the result of the cooperation of all competent parties at the sub-district and village levels. This study aims to analyze the collaboration of the Supervisory Committee for the Election of Governors and Deputy Governors in 2020, Gunungpati District and to understand in depth the flow of information using Social Network Analysis (SNA). The results showed that the overall density of the supervisory committee network was 0.53 or 53%, so the characteristics of the network of members of the Panwaslu Kec.Gunungpati network were in the high category. Panwaslu members with the initials DAP, RV, WPU and M are the most dominant members of the Panwaslu with values of Centrality, Closeness and Betweness Centrality in the network.  

Network Redundancy and Information Diffusion: The Impacts of Information Redundancy, Similarity, and Tie Strength

2016 ◽  
Vol 46 (2) ◽  
pp. 250-272 ◽  
Author(s):  
Hai Liang ◽  
King-wa Fu
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Information Diffusion ◽  
Tie Strength ◽  
Information Redundancy ◽  
Ego Networks ◽  
Core Concepts ◽  
The Impact

It remains controversial whether community structures in social networks are beneficial or not for information diffusion. This study examined the relationships among four core concepts in social network analysis—network redundancy, information redundancy, ego-alter similarity, and tie strength—and their impacts on information diffusion. By using more than 6,500 representative ego networks containing nearly 1 million following relationships from Twitter, the current study found that (1) network redundancy is positively associated with the probability of being retweeted even when competing variables are controlled for; (2) network redundancy is positively associated with information redundancy, which in turn decreases the probability of being retweeted; and (3) the inclusion of both ego-alter similarity and tie strength can attenuate the impact of network redundancy on the probability of being retweeted.

scholarly journals Language, Social Networks, and the City

2021 ◽  
Vol 6 (12) ◽  
pp. 175-185
Author(s):  
Miriam Devaprasana Samuel ◽  
Rita Abdul Rahman Ramakrishna
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Urban Communities ◽  
Post Colonial ◽  
Dense Networks ◽  
Linguistic Patterns ◽  
Diverse Communities ◽  
George Town ◽  
The City

Research in Malaysian sociolinguistics has seen much development pertaining to its concerns over language in its multilingual, multiracial, post-colonial community. The majority of existing literature however tends to lean towards traditional ideologies to explicate the language situation and linguistic patterns taking place within society. As influential as they are, there is a growing need for research to extend and move beyond traditional parameters so as to better explicate the roles and values of language in the increasingly mobile, transnational, diverse communities found in the city. This is certainly true in the historical city of George Town, Penang where exists an eclectic mix of heritage and urbanity – a contest for fluid and fixed notions of identity, culture, traditions, and language. One approach which has been used to contribute towards the study of linguistic patterns is Social Network Analysis. A notable application of analysis network structures is attributed to Milroy (1987), where the following has emerged: close-knit and dense networks are resistant to outside influences whereas loose-knit, weaker network links are embracing of change. This paper therefore aims to explain Social Network Analysis as a framework and method, how it has been applied in previous studies, and the potential it holds to analyse language in contemporary, urban communities as is found in cities like George Town, Penang.

scholarly journals Network Analysis and Actors #CancelOmnibusLaw on Twitter Social Media Using Social Network Analysis (SNA)

2021 ◽  
Vol 4 (3) ◽  
pp. 135-148
Author(s):  
Sabrina Rahma Utami ◽  
Rika Nurismah Safitri ◽  
Yohanes Ari Kuncoroyakti
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Communication Networks ◽  
Communication Theory ◽  
Computer Mediated Communication ◽  
Eigenvector Centrality ◽  
Mediated Communication ◽  
Computer Mediated ◽  
Centrality Analysis

Omnibus Law is the merging of several different rules into one law. RUU Cipta Kerja is one part of the Omnibus Law that attracts attention because it is considered detrimental to society. This caused a lot of rejection and protests from the society. The protest was held directly in the form of demonstrations in various regions of Indonesia and also in Twitter through #BatalkanOmnibusLaw. The purpose of this research is to find out the analysis of communication networks and identify influential actors in #BatalkanOmnibusLaw on Twitter. This research uses Social Network Analysis (SNA) methods and Computer-mediated Communication theory. Data is collected through Twitter from August 1-October 31, 2020. The process of analyzing and retrieving data is using Netlytic.org and Gephi software. The results showed that there were 62 actors with 153 interactions. Proximity between actors is worth 3, meaning close proximity and easy interaction between actors. The interactions created between actors are very few, uneven ,and the interactions that occur only one way. The #BatalkanOmnibusLaw is centered on ten actors, the most dominant account is @fraksirakyatid. Based on degree centrality analysis, closeness centrality, betweenness centrality, and eigenvector centrality the most influential actors in #BatalkanOmnibusLaw network are @fraksirakyatid and @walhinasional. Keywords: #BatalkanOmnibusLaw, Twitter, Actor, Communication Network

scholarly journals Computational Propaganda in Hashtag Activism

2021 ◽  
Vol 13 (2) ◽  
pp. 251
Author(s):  
Andhika Kurniawan Pontoh
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Communication Networks ◽  
Network Structure ◽  
Media Coverage ◽  
Public Attention ◽  
Political Actors ◽  
The Public ◽  
Social Network Structure

The hashtag (#) has an important role in gathering Internet users' support for opinion and value. Computational propaganda has an important role in hashtag activism. This study wants to examine the role of computational propaganda actors such as anonymous political accounts, fake accounts and bot in social media that is able to mobilize the public and also increase the impression of Twitter audiences. The trend of Twitter hashtag activism #BebaskanIBHRS and #NegaraDamaiTanpaFPI began with the arrest of the chairman of the Islamic Defenders Front (FPI) Habib Rizieq Shihab (HRS); the two trending hashtags massively influenced public opinion on Twitter on December 13-14 2020. This study uses a sample of 1000 tweets or conversations on each hashtags and uses Social Network Analysis (SNA) with the Netlytic tool which is able to provide quantitative values of communication networks, through the social network structure of #BebaskaniBHRS and #NegaraDamaiTanpaFPI. This study reveals how the network structure and what factors are carried out by anonymous political actors in carrying out computational propaganda. The results of this study reveal the hashtags activism #BebaskaniBHRS is much more capable of mobilizing the public and is able to generate greater impressions than #NegaraDamaiTanpaFPI. This is because #BebaskaniBHRS has a computational propaganda message in the form of a loaded language with a clear frame and the choice of words directly invites the Twitter public to get involved through a retweet another finding in this research shows computational propaganda movement in hashtag activism was carried out by large groups consisting of anonymous accounts and bot accounts on other side online media coverage about the trending of these hashtag's activism was also able to increasing public attention. Tagar (#) memiliki peran penting dalam mengumpulkan dukungan pengguna Internet terhadap suatu opini dan nilai. Komputasi propaganda memiliki peran penting dalam aktivisme tagar. Penelitian ini ingin mengkaji peran aktor komputasi propaganda seperti akun anonim politik, akun palsu dan bot di media sosial yang mampu memobilisasi publik dan juga meningkatkan kesan khalayak Twitter. Tren aktivisme tagar Twitter #BebaskanIBHRS dan #NegaraDamaiTanpaFPI dimulai dengan penangkapan ketua Front Pembela Islam (FPI) Habib Rizieq Shihab (HRS); kedua tagar yang sedang trending tersebut secara masif memengaruhi opini publik di Twitter pada 13-14 Desember 2020. Penelitian ini menggunakan sampel 1000 tweet atau percakapan pada masing-masing tagar serta menggunakan Social Network Analysis (SNA) dengan alat Netlytic yang mampu memberikan nilai kuantitatif jaringan komunikasi. Melalui struktur jejaring sosial #BebaskaniBHRS dan #NegaraDamaiTanpaFPI, kajian ini mengungkap seperti apa struktur jaringan komunikasi dan hal apa saja yang dilakukan oleh aktor politik anonim dalam melakukan komputasi propaganda. Hasil penelitian ini mengungkapkan bahwa aktivisme tagar #BebaskaniBHRS jauh lebih mampu memobilisasi publik dan mampu menghasilkan impresi yang lebih besar dibandingkan #NegaraDamaiTanpaFPI. Hal ini dikarenakan #BebaskaniBHRS memiliki pesan komputasi propaganda dalam bentuk bahasa yang sarat dengan bingkai yang jelas dan pilihan kata secara langsung mengajak publik Twitter untuk terlibat melalui retweet.Temuan lain dalam penelitian ini menunjukkan gerakan komputasi propaganda dalam aktivisme  tagar dilakukan oleh kelompok besar yang terdiri dari akun anonim dan akun bot di sisi lain liputan media daring tentang tren aktivisme tagar ini juga mampu meningkatkan atensi publik.

scholarly journals Informatics for COVID-19 in New York and California

2021 ◽  
pp. 1-14
Author(s):  
Seungil Yum
Keyword(s):  
New York ◽  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Communication Networks ◽  
Crucial Role ◽  
Essential Role ◽  
The Us ◽  
Key Players

Abstract Objective: This study explores how social networks for COVID-19 are differentiated by regions. Methods: This study employs social network analysis for Twitter in New York and California. Results: National key players play an important role in New York, while regional key players exert a significant impact on California. Some key players, such as the US president, play an essential role in both New York and California. Hispanic key players play a crucial role in California. Each group is more likely to show communication networks within groups in New York, while it is more apt to exhibit communication networks across groups in California. Government players play a different role in social networks according to regions. Conclusions: Governments should understand how social networks for COVID-19 are differentiated by regions to control the ongoing pandemic effectively.

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