Refusing to be safe. The Social Network Communication of deniers

[EN] This essay aims at showing the results of an analysis concerning communication on social networks by focusing on the collection of comments related to the pandemic. The analysis describes the structure of the communication, showing the presence of parallel communities and the different configuration of relational dynamics, selected contents, flows of communication, category of users and language. Complex network structures are identified branching from keywords like no-mask, covid-19, greenpass. Further attention is paid to the connection between online communication and the triggering of protests.D'agata, R.; Gozzo, S. (2022). Refusing to be safe. The Social Network Communication of deniers. En 4th International Conference on Advanced Research Methods and Analytics (CARMA 2022). Editorial Universitat Politècnica de València. 267-275. http://hdl.handle.net/10251/18957126727

A Twitter Social Network analysis based on graph and network theory : the South African Health Insurance Bill Case

Abstract:Social Network Analysis (SNA) is the process of extricating relationships and interchanges among firms, individuals and connected information objects by way of visual mapping. Through the lenses of graph theory and network theory, this study aims to explore the Twitter social media network shortly after the introduction of the National Health Insurance (NHI) Bill to the South African parliament was announced for debate. In graph theory, algorithms are used to extract knowledge and efficient visualisation techniques to represent, for the purpose of this study, pairwise relations between objects, namely Twitter data. An instrumental, single case study design and SNA (based on network theory principles) secured contextual and timely Twitter interchanges of 4 112 tweets of the hashtag “NHI”. The uniqueness of this inquiry is the use of the ‘Network Overview, Discovery and Exploration for Excel Pro’ (NodeXL Pro) tool for social media analytics to simplify the Twitter SNA tasks and analysis of the #NHI twitter social media network. The findings explain the data dispersion and network structure of the #NHI case. The significance of the study is that the SNA clearly identifies the influencers, popular Twitter users and gatekeepers in the announcement of a highly controversial healthcare bill that will affect all South African citizens

ADOPSI SOCIAL NETWORK ANALYSIS (SNA) DALAM UPAYA MEMBANGUN KETANGGUHAN BENCANA di MASYARAKAT

Pembangunan ketangguhan bencana merupakan strategi untuk kesiapan bencana. Ketangguhan masyarakat, dalam istilah sosiologis, adalah kemampuan komunitas atau sosial unit untuk menahan guncangan eksternal, seperti bencana, terhadap infrastrukturnya. Peningkatan inkremental dalam ketangguhan dapat secara signifikan meningkatkan kapasitas komunitas untuk mempersiapkan, menanggapi, dan memulihkan diri dari bencana. Kecepatan komunitas dapat memobilisasi dan menggunakan sumber daya selama dan setelah bencana sangat tergantung pada kemampuannya untuk beradaptasi dengan perubahan. Kekuatan jejaring sosial adalah faktor utama yang akan membangunkan dari keterpurukan pasca bencana. SNA (Social Network Analysis) merupakan suatu teknik untuk memetakan dan mengukur relasi dan komunikasi yang terjadi antar manusia, kelompok, organisasi, komputer ataupun entitas yang memproses suatu informasi. SNA dapat diterapkan selama semua fase siklus bencana. Adopsi SNA memiliki potensi untuk merevolusi cara organisasi dan masyarakat berfungsi secara umum, dan mempersiapkan dan menanggapi bencana secara spesifik

#Liberty breach: An exploratory usage case of NodeXL Pro as a social media analytics tool for Twitter

Abstract: Social media analytics uses data mining tools, platforms, and analytics techniques to collect and analyse infinite amounts of social media data. Social media analytics tools extract patterns and connections from data, for insight into market sentiments and requirements, to enhance business intelligence. ‘Network Overview, Discovery and Exploration for Excel Pro’ (NodeXL Pro) is a social media analytics tool that simplifies basic network analysis tasks and supports the analysis of social media networks. NodeXL Pro does sophisticated ‘crawling’ (extracting data) across a range of social media platforms. Through a qualitative case study design, this study explores and describes the use of NodeXL Pro through empirical and multimodal analysis and social network visualisation of social media data of the Liberty Holdings Ltd data breach crisis case in June 2018. The hashtag ‘#Liberty breach’ resulted in 10 000 data sources (‘tweets’) from the social media platform Twitter. This study is unique on two levels. Firstly, it appears to be the first study in the South African marketing literature to use NodeXL Pro in social media analytics. Secondly, it presents the case study as a usage case to describe, in a step‐by‐step way, the functionalities of NodeXL Pro through social network analysis. The main finding of the paper focuses on the usability and manifold features (including the integrated visualisation tool) of NodeXL Pro. This social media analytics tool can open doors for marketing scholars and practitioners alike to measure, map, and model collections of connections

Korean popular culture analytics in social media streaming: evidence from YouTube channels in Thailand

This research aimed to study and analyze the influence and impact of Korean popular culture (K-pop) on Thai society. In this study, we used Social Network Analysis (SNA) to analyze streaming data obtained from a variety of YouTube channels belonging to YouTubers across the world, text analytics to analyze demographic characteristics, YouTuber's presentation techniques, as well as subscriber behavior, and multiple correlations analysis to analyze the relationship between factors affecting YouTube Channels in Thailand. The findings revealed that five Thai YouTube Channels were influencing Thai society. Furthermore, there were robust positive correlations between the number of dislikes and the number of comments (0.79), and the number of likes and comments (0.65). Additionally, there was a positive correlation between the number of views and the number of dislikes and one between the number of likes and dislikes. Future research can supplement the present findings with other social media sources to yield an even more diverse and comprehensive analysis. These analytics can be applied to various situations, including corporate marketing strategies, political campaigns, or disease/symptom analysis in medicine. This research extends to social computing by revealing intelligent trends in social networks

A Bibliometric Study of Social Media as a e-Government Public Services

Social media is used as an essential tool of government communication to the public and a form of service from e-government. This paper aims to identify the scientific development of social media themes in public communication services. This paper used bibliometric technic to investigate the broad overview of media studies on government public services. The analysis includes a citation and co-citation analysis, bibliographical coupling, and co-occurrence analysis. The data is taken from the Scopus database for 2010- 2021 with the source of the journal article type. The analysis results show the dynamics of increasing and decreasing the number of government social media studies. The bibliometric analysis also shows the most contributing journal sources, the most productive authors, the most cited journal articles, co-citations between authors, and clusters of themes that develop from social media themes used by the government in communicating and serving the public

Unlocking the power of Twitter communities for startups

Peixoto, A. R., Almeida, A. D., António, N., Batista, F., Ribeiro, R., & Cardoso, E. (2023). Unlocking the power of Twitter communities for startups. Applied Network Science, 8, 1-21. [66]. https://doi.org/10.21203/rs.3.rs-3062630/v1, https://doi.org/10.1007/s41109-023-00593-0 --- This work was partially supported by Fundação para a Ciência e a Tecnologia, I.P. (FCT) namely by UIDB/04466/2020 and UIDP/04466/2020 (ISTAR_Iscte); UIDB/04152/2020 (MagIC/NOVA IMS); UIDB/50021/2020 (INESC-ID); and UIDB/03126/2020 (CIES_Iscte).Social media platforms offer cost-effective digital marketing opportunities to monitor the market, create user communities, and spread positive opinions. They allow companies with fewer budgets, like startups, to achieve their goals and grow. In fact, studies found that startups with active engagement on those platforms have a higher chance of succeeding and receiving funding from venture capitalists. Our study explores how startups utilize social media platforms to foster social communities. We also aim to characterize the individuals within these communities. The findings from this study underscore the importance of social media for startups. We used network analysis and visualization techniques to investigate the communities of Portuguese IT startups through their Twitter data. For that, a social digraph has been created, and its visualization shows that each startup created a community with a degree of intersecting followers and following users. We characterized those users using user node-level measures. The results indicate that users who are followed by or follow Portuguese IT startups are of these types: “Person”, “Company,” “Blog,” “Venture Capital/Investor,” “IT Event,” “Incubators/Accelerators,” “Startup,” and “University.” Furthermore, startups follow users who post high volumes of tweets and have high popularity levels, while those who follow them have low activity and are unpopular. The attained results reveal the power of Twitter communities and offer essential insights for startups to consider when building their social media strategies. Lastly, this study proposes a methodological process for social media community analysis on platforms like Twitter.publishersversionpublishe

Examining the information dissemination process on social media during the Malaysia 2014 floods using Social Network Analysis (SNA)

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

A Complex Social Network Analyses of Online Finanical Communties in Times of Geopolitcal Military and Terrorist Events

Given the advances in technology the field of social network analysis has very much hit the forefront in recent years. The information age harnesses the use of social network analysis for multiple industries and for solving complex problems. Social network analysis is an important tool in the world of the military and counter intelligence, whether it’s the capture of Osama Bin Laden or uncovering hidden Al Qaeda terrorist networks, the world around us is built on networks, be that hidden or otherwise. Online social networks give new information in the world of intelligence agencies similarly online financial communities such as Yahoo Finance gives intelligent information to knowledge hungry investors. This thesis is concerned with the exploration and exploitation of online financial community dynamics and networks using social network analysis (SNA) as a mechanism. Social network analysis measurement techniques will be applied to understand the reaction of online investors to military and terrorist geopolitical events, the stock market’s reaction to these events and if it is possible to predict military stock prices after military and terrorist geopolitical events