scholarly journals Individuals’ Use of Twitter to Discuss Freedom of Information in the United States: A Social Network Analysis

2019 ◽  
Vol 1 (2) ◽  
pp. 45-59
Author(s):  
Kayla Schwoerer
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
The United States ◽  
Freedom Of Information ◽  
Public Agencies ◽  
Freedom Of Information Act ◽  
Advocacy Organizations ◽  
The U.S

This study employs social network analysis to examine more than 10,000 Twitter interactions that include the U.S. Freedom of Information Act hashtag (#FOIA) to understand who is engaging online, and to what extent. The analysis finds evidence of a dynamic conversation online among citizens, journalists, advocates, and public agencies. Findings offer insights into how citizens are using social media to engage with government and one another in conversations around important public policies, such as government transparency, as well as how technologies such as social media can be leveraged to better understand citizens’ interest. The study also found a significant increase in tweets during national Sunshine Week, a vehicle that increases national dialogue about FOI, and highlights effective social media strategies employed by MuckRock and other advocacy organizations.

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.

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 Sustainable Tourism Empowered by Social Network Analysis to Gain a Competitive Edge at a Historic Site

2021 ◽  
Vol 2 (4) ◽  
pp. 332-346
Author(s):  
Cathrine Linnes ◽  
Holly Itoga ◽  
Jerome Agrusa ◽  
Joseph Lema
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Tourism Industry ◽  
Tourism Destination ◽  
Strategic Direction ◽  
Social Media Platforms ◽  
Hospitality And Tourism Industry ◽  
Effective Use

Social media has had a strong presence in many people’s lives over the last decade. In addition, social media platforms have allowed people to share opinions, provide advice on numerous factors, including where to visit, as well as to stay connected and maintain friendships. The hospitality and tourism industry, however, can make effective use of these powerful tools for marketing purposes, collaboration and information sharing, and service offerings. Reviewing social media followers’ behaviors and interests offers a wealth of information and valuable data for a variety of tourism organizations. This case study focuses on an analysis of the social networks applied to the fortified town of Fredrikstad in Norway. The data used in this research study were collected from the Facebook site of the tourist authority. The results of this research project demonstrate the strengths of applying a social network analysis to a dataset, which can aid in the strategic direction of a tourism destination. The conversations of the greatest interest can successfully be identified as well as the growth of the online network. This paper adds knowledge to the literature through the application of a social network analysis regarding the success of a tourism destination and its future potential.

scholarly journals Application of social network analysis for determining the suitable social media influencers

2021 ◽  
Vol 10 (6) ◽  
pp. 348-354
Author(s):  
Mochamad Yudha Febrianta ◽  
Yusditira Yusditira ◽  
Sri Widianesty
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Marketing Strategy ◽  
Marketing Strategies ◽  
The Other ◽  
Social Media Marketing ◽  
Other Hand ◽  
The Social

Virtual Hotel Operator (VHO) trend is growing rapidly, especially in Indonesia. Two of the most popular VHO in Indonesia are OYO and RedDoorz, both have been competing to attain the first position. Both OYO and RedDoorz have their own social media marketing strategies. For example, OYO persuades other conventional hotels to collaborate and use the OYO platform in their businesses. On the other hand, RedDoorz was recorded as the most visited Virtual Hotel Operator Platform in 2019, based on the data of Konsumen Jakpat 2019. OYO and RedDoorz also utilize social media to promote their services such as Instagram and Twitter. For advertising their businesses in social media, OYO and RedDoorz often use some social media influencers or known as influencer social media marketing. Influencers should be able to effectively deliver the messages and influence people’s decisions to use the products or services they advertise. This study aims to further explore the social media marketing strategy employed by OYO and RedDoorz. The results of Social Network Analysis by using “oyoindonesia” and ‘reddoorz’ as keywords in social media Twitter showed that RedDoorz has a bigger social network and more users involved in spreading their information than OYO. On the other hand, OYO's official account on Twitter is more efficient in performing its function as marketing media.

Social network analysis and data visualization of MIS international collaboration in Taiwan

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yung-Ting Chuang ◽  
Yi-Hsi Chen
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
International Collaboration ◽  
Research Productivity ◽  
Research Collaboration ◽  
Clustering Algorithms ◽  
The United States ◽  
Content Type ◽  
Collaboration Patterns

PurposeThe purpose of this paper is to apply social network analysis (SNA) to study faculty research productivity, to identify key leaders, to study publication keywords and research areas and to visualize international collaboration patterns and analyze collaboration research fields from all Management Information System (MIS) departments in Taiwan from 1982 to 2015.Design/methodology/approachThe authors first retrieved results encompassing about 1,766 MIS professors and their publication records between 1982 and 2015 from the Ministry of Science and Technology of Taiwan (MOST) website. Next, the authors merged these publication records with the records obtained from the Web of Science, Google Scholar, IEEE Xplore, ScienceDirect, Airiti Library and Springer Link databases. The authors further applied six network centrality equations, leadership index, exponential weighted moving average (EWMA), contribution value and k-means clustering algorithms to analyze the collaboration patterns, research productivity and publication patterns. Finally, the authors applied D3.js to visualize the faculty members' international collaborations from all MIS departments in Taiwan.FindingsThe authors have first identified important scholars or leaders in the network. The authors also see that most MIS scholars in Taiwan tend to publish their papers in the journals such as Decision Support Systems and Information and Management. The authors have further figured out the significant scholars who have actively collaborated with academics in other countries. Furthermore, the authors have recognized the universities that have frequent collaboration with other international universities. The United States, China, Canada and the United Kingdom are the countries that have the highest numbers of collaborations with Taiwanese academics. Lastly, the keywords model, system and algorithm were the most common terms used in recent years.Originality/valueThis study applied SNA to visualize international research collaboration patterns and has revealed some salient characteristics of international cooperation trends and patterns, leadership networks and influences and research productivity for faculty in Information Management departments in Taiwan from 1982 to 2015. In addition, the authors have discovered the most common keywords used in recent years.

An Experimental Evaluation of Link Prediction for Movie Suggestions Using Social Media Content

2018 ◽  
pp. 203-230
Author(s):  
Anu Taneja ◽  
Bhawna Gupta ◽  
Anuja Arora
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Online Social Networks ◽  
Experimental Evaluation ◽  
Link Prediction ◽  
Common Neighbor ◽  
Research Directions ◽  
Definition Of

The enormous growth and dynamic nature of online social networks have emerged to new research directions that examine the social network analysis mechanisms. In this chapter, the authors have explored a novel technique of recommendation for social media and used well known social network analysis (SNA) mechanisms-link prediction. The initial impetus of this chapter is to provide general description, formal definition of the problem, its applications, state-of-art of various link prediction approaches in social media networks. Further, an experimental evaluation has been made to inspect the role of link prediction in real environment by employing basic common neighbor link prediction approach on IMDb data. To improve performance, weighted common neighbor link prediction (WCNLP) approach has been proposed. This exploits the prediction features to predict new links among users of IMDb. The evaluation shows how the inclusion of weight among the nodes offers high link prediction performance and opens further research directions.

Measuring the Impact of Social Media

2011 ◽  
pp. 24-36 ◽  
Author(s):  
Kimiz Dalkir
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Evaluation Method ◽  
Real Life ◽  
Work Processes ◽  
The Social ◽  
Post Test ◽  
The Impact

This chapter focuses on a method, social network analysis (SNA) that can be used to assess the quantity and quality of connection, communication and collaboration mediated by social tools in an organization. An organization, in the Canadian public sector, is used as a real-life case study to illustrate how SNA can be used in a pre-test/post-test evaluation design to conduct a comparative assessment of methods that can be used before, during and after the implementation of organizational change in work processes. The same evaluation method can be used to assess the impact of introducing new social media such as wikis, expertise locator systems, blogs, Twitter and so on. In other words, while traditional pre-test/post-test designs can be easily applied to social media, the social media tools themselves can be added to the assessment toolkit. Social network analysis in particular is a good candidate to analyze the connections between people and content as well as people with other people.

Sign in / Sign up

Export Citation Format

Share Document