Understanding user behavior in a local social media platform by social network analysis

Tang, Tingan; Hämäläinen, Matti; Virolainen, Antti; Makkonen, Juho

doi:10.1145/2181037.2181067

Cited by 9 publications

(9 citation statements)

References 11 publications

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“…The use of NodeXL was also recently highlighted in a study which identified polarised crowds and opinion leaders in topics related to a viral hashtag on Twitter around abortion titled “#ShoutYourAbortion” (Ahmed, 2018). NodeXL in academic work has also ranged from the analysis of blackboard discussion boards (Waters and Gasson, 2012), blogs (Saffer, 2013), personal e-mail networks (Bengfort and Xirogiannopoulos, 2015), internal security (Gamachchi et al , 2017), medical data analysis (Piepoli et al , 2012), political sponsorship (Piepoli et al , 2012), news stories (Quinn and Powers, 2016), campus-based social media platforms (Tang et al , 2011) and Wikipedia (Ferron and Massa, 2011).…”

Section: Resultsmentioning

confidence: 99%

Social media analytics: analysis and visualisation of news diffusion using NodeXL

Ahmed

Lugović

2019

OIR

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The purpose of this paper is to provide an overview of NodeXL in the context of news diffusion. Journalists often include a social media dimension in their stories but lack the tools to get digital photos of the virtual crowds about which they write. NodeXL is an easy to use tool for collecting, analysing, visualizing, and reporting on the patterns found in collections of connections in streams of social media. With a network map patterns emerge that highlight key people, groups, divisions and bridges, themes and related resources. Design/methodology/approach: This study conducts a literature review of previous empirical work which has utilised NodeXL and highlights the potential of NodeXL to provide network insights of virtual crowds during emerging news events. It then develops a number of guidelines which can be utlised by news media teams to measure and map information diffusion during emerging news events. Findings: One emergent software application known as NodeXL has allowed journalists to take 'group photos' of the connections among a group of users on social media. It was found that a diverse range of disciplines utilise NodeXL in academic research. Furthermore based on the features of NodeXL a number of guidelines were developed which provide insight into how to measure and map emerging news events on Twitter. Social implications: With a set of social media network images a journalist can cover a set of social media content streams and quickly grasp "situational awareness" of the shape of the crowd. Since social media popular support is often cited but not documented, NodeXL social media network maps can help journalists quickly document the social landscape utilising an innovative approach. Originality/value: This is the first empirical study to review literature on NodeXL, and to provide insight into the value of network visualisations and analytics for the news media domain. Moreover, it is the first empirical study to develop guidelines that will act as a valuable resource for newsrooms looking to acquire insight into emerging news events from the stream of social media posts. In the era of fake news and automated accounts i.e., bots the ability to highlight opinion leaders and ascertain their allegiances will be of importance in today's news climate.

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Section: Resultsmentioning

confidence: 99%

Social media analytics: analysis and visualisation of news diffusion using NodeXL

Ahmed

Lugović

2019

OIR

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“…Lo et al [48] conducted a study on Hong Kong visitors which revealed that over 89% of visitors take photos; however, only 41% are willing to post them online, with results indicating that those who posted opted to post the photos on social media sites. Furthermore, Tang et al [49] analyzed user behaviors by applying social network research to a university campus-based social media site on which personal items and resources are exchanged, with findings indicating that user experiences remained highly positive. When applying social network analysis, however, Tang et al [49] suggested using Facebook or Twitter as platforms for analysis.…”

Section: Collaboration Knowledge and Information-sharingmentioning

confidence: 99%

“…Furthermore, Tang et al [49] analyzed user behaviors by applying social network research to a university campus-based social media site on which personal items and resources are exchanged, with findings indicating that user experiences remained highly positive. When applying social network analysis, however, Tang et al [49] suggested using Facebook or Twitter as platforms for analysis. Rathonyi [50] explored visitor motivation to share information, with survey findings reporting that both the bulk of students using social networking websites daily and students who did not use the same channels for planning a trip preferred to ask fellow students, friends, and relatives for recommendations.…”

Section: Collaboration Knowledge and Information-sharingmentioning

confidence: 99%

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

Linnes

Itoga

Agrusa

et al. 2021

Tourism and Hospitality

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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.

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“…Social networks according to [16] are an avenue through which users are able to share data and information that can be in the form of audio, video, picture or text. Users connect with each other by forming edges, which allow information to be transferred.…”

Section: A Social Networkmentioning

confidence: 99%

Influence Maximization Towards Target Users on Social Networks for Information Diffusion

Olanrewaju

Ahmad

Mahmudin

2017

Recent Trends in Information and Communication Technology

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Influence maximisation has been an area of active research in recent years. This study aims to extend the fundamental influence maximisation problem (IMP) with respect to a set of target users on a social network. It is important to aim at the target users to speed up the rate of information diffusion and reduce the information diffusion cost. In doing so, the MITU algorithm was formulated and compared with state of the art algorithms. Publicly available datasets were used in validating the proposed algorithm. It was found that the MITU identified all target nodes while significantly lowering the information diffusion cost function (IDCF) by up to 79%. The influence overlap problem was equally identified in the heuristic algorithm where the seed set size was reduced by an average of six times. Furthermore, the random influencer selection identifies target nodes better than the betweenness and PageRank centralities. The findings could help organisations to reach target users on social media in the shortest cycle.

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Understanding user behavior in a local social media platform by social network analysis

Cited by 9 publications

References 11 publications

Social media analytics: analysis and visualisation of news diffusion using NodeXL

Social media analytics: analysis and visualisation of news diffusion using NodeXL

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

Influence Maximization Towards Target Users on Social Networks for Information Diffusion

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