INFORMATION EXCHANGES OF SOCIAL MEDIA EVANGELISTS DURING FLOOD: A SOCIAL NETWORK ANALYSIS

2016 ◽  
Vol 78 (9-3) ◽  
Author(s):  
Abdus-samad Temitope Olanrewaju ◽  
Rahayu Ahmad ◽  
Kamarul Faizal Hashim
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Structure ◽  
Information Dissemination ◽  
Network Structures ◽  
Analysis Technique ◽  
Types Of Information ◽  
Information Brokers

Information dissemination during disaster is very crucial, but inherits several complexities associated with the dynamic characteristics of the disaster. Social media evangelists (activists) play an important role in disseminating critical updates at on-site locations. However, there is limited understanding on the network structure formed and its evolution and the types of information shared. To address these questions, this study employs Social Network Analysis technique on a dataset containing 157 social media posts from an influential civilian fan page during Malaysia’s flood. The finding demonstrates three different network structures emerged during the flood period. The network structure evolves depending on the current state of the flood, the amount of information available and the need of information. Through content analysis, there were seven types of information exchanges discovered. These information exchanges evolved as the scale and magnitude of flood changes. In conclusion, this study shows the emergence of different network structures, density and identification of influential information brokers among civilians that use social media during disaster. Despite the low number of influential information brokers, they successfully manage their specific cluster in conveying information about the disaster and most importantly coordinating the rescue mission.

scholarly journals Analisis Akun Twitter Berpengaruh terkait Covid-19 menggunakan Social Network Analysis

2021 ◽  
Vol 5 (4) ◽  
pp. 697-704
Author(s):  
Aprillian Kartino ◽  
M. Khairul Anam ◽  
Rahmaddeni ◽  
Junadhi
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Information Dissemination ◽  
Interaction Network ◽  
Analysis Method ◽  
The Social ◽  
The World ◽  
High Degree

Covid-19 is a disease of the virus that is shaking the world and has been designated by WHO as a pandemic. This case of Covid-19 can be a place of dissemination of disinformation that can be utilized by some parties. The dissemination of information in this day and age has turned to the internet, namely social media, Twitter is one of the social media that is often used by Indonesians and the data can be analyzed. This study uses the social network analysis method, conducted to be able to find nodes that affect the ongoing interaction in the interaction network of information dissemination related to Covid-19 in Indonesia and see if the node is directly proportional to the value of its popularity. As well as to know in identifying the source of Covid-19 information, whether dominated by competent Twitter accounts in their fields. The data examined 19,939 nodes and 12,304 edges were taken from data provided by the web academic.droneemprit.id on the project "Analisis Opini Persebaran Virus Corona di Media Sosial", using the period of December 2019 to December 2020 on social media Twitter. The results showed that the @do_ra_dong account is an influential actor with the highest degree centrality of 860 and the @detikcom account is the actor with the highest popularity value of follower rank of 0.994741605. Thus actors who have a high degree of centrality value do not necessarily have a high follower rank value anyway. The study ignores if there are buzzer accounts on Twitter.  

scholarly journals A Social Network Analysis: Identifying Influencers in The COVID-19 Vaccination Discussion on Twitter

Compiler ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 99
Author(s):  
Muhammad Habibi ◽  
Puji Winar Cahyo
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Information Dissemination ◽  
User Behavior ◽  
Online News ◽  
Social Media Analytics ◽  
Government Organizations ◽  
The Republic

Social media analytics, especially Twitter, has experienced significant growth over the last few years. The data generated by Twitter provides valuable information to many stakeholders regarding user behavior, preferences, tastes, and characteristics. The presence of influencers on social media can invite interaction with other users. An influencer can affect the speed of spreading information on social media. This study looks at the influence of influencers and information dissemination channels on Twitter data related to COVID-19 vaccination in Indonesia as one of the hot Twitter discussion trends. This study applies Social Network Analysis (SNA) as a theoretical and methodological framework to show that interactions between users have differences on the network when the analyzed tweets are divided into mention and retweet networks. This study found that the key accounts in disseminating information related to Covid-19 vaccination were dominated by official accounts of government organizations and online news portals. The official Twitter account of government organizations turns out to have an essential role in disseminating information related to COVID-19 vaccination, namely the @KemenkesRI account belonging to the Ministry of Health of the Republic of Indonesia and the @Puspen_TNI account belonging to the TNI Information Center.

scholarly journals Exploring Crisis Communication and Information Dissemination on Social Media: Social Network Analysis of Hurricane Irma Tweets

2020 ◽  
Vol 3 (2) ◽  
pp. 179-210 ◽  
Author(s):  
Xianlin Jin
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Crisis Communication ◽  
Information Diffusion ◽  
Information Dissemination ◽  
Opinion Leader ◽  
Communication Model ◽  
Hurricane Irma

This study utilized social network analysis to identify the top 10 Twitter influentials during the Hurricane Irma crisis period and examined the relationship between social media attributes and the bridge influence of controlling information flow. The number of a user’s followers and tweets significantly predicted one’s control of information. Crisis information tended to be shared in scattered subgroups. Social network boundaries impeded information diffusion, and the communication pattern was largely one-way. The findings partially supported the opinion leader argument while indicating that influentials can directly generate information, which is consistent with the social-mediated crisis communication model. Such findings will contribute to crisis literature and help emergency management professionals advance social media usage to disseminate crisis information, build effective communication, and provide immediate disaster relief responses

How to Study Online Networking

2022 ◽  
pp. 360-374
Author(s):  
Fabio Corbisiero
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Information Dissemination ◽  
Field Research ◽  
Social Phenomena ◽  
The Past ◽  
Network Research

Social media and social networks are pervasive in the daily use as well as in a number of applications. Social media and social networks are also intertwined, as the social medial platforms also offer the opportunity to develop and analyze social networks. Over the past two decades, there has been an explosion of interest in network research through social network analysis. Network research is “warm” today, with the number of articles on the topic of social media and social networks nearly tripling in the past decade. This interweaving has been a further breakthrough within field research yielding explanations for social phenomena in a wide variety of new ways. Social network analysis (SNA) has been recognized as a powerful tool for representing social network structures and information dissemination on the web. Here, the authors review the kinds of things that sociologists have tried to explain using social network analysis and provide a nutshell description of the basic assumptions, goals, and explanatory mechanisms prevalent in the field, with emphasis on SNA research methodology.

scholarly journals EXAMINING THE INFORMATION DISSEMINATION PROCESS ON SOCIAL MEDIA DURING THE MALAYSIA 2014 FLOODS USING SOCIAL NETWORK ANALYSIS (SNA)

2017 ◽  
Author(s):  
Abdus-Samad Temitope Olanrewaju ◽  
Rahayu Ahmad
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Information Dissemination ◽  
Governmental Organization ◽  
The Social ◽  
Dissemination Process ◽  
Information Providers

This article is based on a study which examined the information dissemination process on the social media during the Malaysia 2014 floods by employing the Social Network Analysis. Specifically, the study analyzed the type of network structure formed and its density, the influential people involved, and the kind of information shared during the flood. The data was collected from a non-governmental organization fan page (NGOFP) and a significant civilian fan page (ICFP) on Facebook using NodeXL. The two datasets contained 296 posts which generated different network structures based on the state of the flood, information available, and the needs of the information. Through content analysis, five common themes emerged from the information exchanges for both fan pages which helped in providing material and psychological support to the flood victims. However, only 5% of the networks’ population served as information providers, and this prompted the need for more active participation especially from organizations with certified information. Based on the findings presented and elaborated, this article concluded by stating the implications and recommendations of the study conducted.  

Assessing Risk Communication in Social Media for Crisis Prevention: A Social Network Analysis of Microblog

2017 ◽  
Vol 14 (1) ◽  
Author(s):  
Jia Shi ◽  
Naim Kapucu ◽  
Zhengwei Zhu ◽  
Xuesong Guo ◽  
Brittany Haupt
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Risk Perception ◽  
Network Analysis ◽  
Risk Communication ◽  
Crisis Management ◽  
Network Structure ◽  
Information Resources ◽  
Crisis Prevention

AbstractThis article examines risk communication and perception differences via social media in the context of crisis management. Based on data from the Shifang Protest, this study constructed a relational matrix identifying how critical actors facilitated risk communication and interactions. In addition, the article identified measures of network structure and risk perception differences with Social Network Analysis (i.e. density, centralization, structure holes and subgroups) using UCINET software program along visual structures with NetDraw. Key findings of this study include: a) ranked actors controlled most of the information resources and threat diffusion; b) the level of interaction between government users and others users is extremely low; and c) divergence occurred between personal (informal) and official (formal) nodes in the context of risk perception.

ANALISIS PERINGKAT TOP BRAND OJEK ONLINE MENGGUNAKAN JEJARING SOSIAL PERCAKAPAN TWITTER

2019 ◽  
Vol 24 (2) ◽  
pp. 88-104
Author(s):  
Ilham Aminudin ◽  
Dyah Anggraini
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Path Length ◽  
Average Path Length ◽  
Average Degree ◽  
Clustering Coefficient ◽  
R Programming

Banyak bisnis mulai muncul dengan melibatkan pengembangan teknologi internet. Salah satunya adalah bisnis di aplikasi berbasis penyedia layanan di bidang moda transportasi berbasis online yang ternyata dapat memberikan solusi dan menjawab berbagai kekhawatiran publik tentang layanan transportasi umum. Kemacetan lalu lintas di kota-kota besar dan ketegangan publik dengan keamanan transportasi umum diselesaikan dengan adanya aplikasi transportasi online seperti Grab dan Gojek yang memberikan kemudahan dan kenyamanan bagi penggunanya Penelitian ini dilakukan untuk menganalisa keaktifan percakapan brand jasa transportasi online di jejaring sosial Twitter berdasarkan properti jaringan. Penelitian dilakukan dengan dengan mengambil data dari percakapan pengguna di social media Twitter dengan cara crawling menggunakan Bahasa pemrograman R programming dan software R Studio dan pembuatan model jaringan dengan software Gephy. Setelah itu data dianalisis menggunakan metode social network analysis yang terdiri berdasarkan properti jaringan yaitu size, density, modularity, diameter, average degree, average path length, dan clustering coefficient dan nantinya hasil analisis akan dibandingkan dari setiap properti jaringan kedua brand jasa transportasi Online dan ditentukan strategi dalam meningkatkan dan mempertahankan keaktifan serta tingkat kehadiran brand jasa transportasi online, Grab dan Gojek.

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