Investigating the Greek political Twittersphere: Greek MPs and their Twitter network

Kleftodimos, Alexandros; Lappas, Georgios; Triantafyllidou, Amalia; Yannacopoulou, Anastasia

doi:10.23919/seeda-cecnsm.2018.8544945

Cited by 3 publications

(2 citation statements)

References 20 publications

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“…e work of [33,34] investigated the aspect of the Greek MPs Twitter network. ey studied MPs (members of parliament) who belonged to the two major parties of Greek.…”

Section: Related Workmentioning

confidence: 99%

Predicting Politician’s Supporters’ Network on Twitter Using Social Network Analysis and Semantic Analysis

Khan

Zhang

Shang

et al. 2020

Scientific Programming

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Politics is one of the hottest and most commonly mentioned and viewed topics on social media networks nowadays. Microblogging platforms like Twitter and Weibo are widely used by many politicians who have a huge number of followers and supporters on those platforms. It is essential to study the supporters’ network of political leaders because it can help in decision making when predicting their political futures. This study focuses on the supporters’ network of three famous political leaders of Pakistan, namely, Imran Khan (IK), Maryam Nawaz Sharif (MNS), and Bilawal Bhutto Zardari (BBZ). This is done using social network analysis and semantic analysis. The proposed method (1) detects and removes fake supporter(s), (2) mines communities in the politicians’ social network(s), (3) investigates the supporters’ reply network for conversations between supporters about each leader, and, finally, (4) analyses the retweet network for information diffusion of each political leader. Furthermore, sentiment analysis of the supporters of politicians is done using machine learning techniques, which ultimately predicted and revealed the strongest supporter network(s) among the three political leaders. Analysis of this data reveals that as of October 2017 (1) IK was the most renowned of the three politicians and had the strongest supporter’s community while using Twitter in a very controlled manner, (2) BBZ had the weakest supporters’ network on Twitter, and (3) the supporters of the political leaders in Pakistan are flexible on Twitter, communicating with each other, and that any group of supporters has a low level of isolation.

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“…e work of [33,34] investigated the aspect of the Greek MPs Twitter network. ey studied MPs (members of parliament) who belonged to the two major parties of Greek.…”

Section: Related Workmentioning

confidence: 99%

Predicting Politician’s Supporters’ Network on Twitter Using Social Network Analysis and Semantic Analysis

Khan

Zhang

Shang

et al. 2020

Scientific Programming

View full text Add to dashboard Cite

show abstract

“…This research suggests that networks can be revealed even through subtle, indirect messaging on Twitter. Rojas and Boguslavskaya (2018) studied the participation of women in the political discussion on social media, suggesting that traditional alliances are disrupted by the new media, and Kleftodimos et al (2018) examine the Greek political Twittersphere, recognizing previously unseen interconnections. Social media is also heavily used in the preparation for, and aftermath of, natural disasters.…”

Section: Literature Reviewmentioning

confidence: 99%

Religious Violence and Twitter: Networks of Knowledge, Empathy and Fascination

2022

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Twitter analysis through data mining, text analysis, and visualization, coupled with the application of actor-network-theory, reveals a coalition of heterogenous religious affiliations around grief and fascination. While religious violence has always existed, the prevalence of social media has led to an increase in the magnitude of discussions around the topic. This paper examines the different reactions on Twitter to violence targeting three religious communities: the 2015 Charleston Church shooting, the 2018 Pittsburgh Synagogue shooting, and the 2019 Christchurch Mosque shootings. The attacks were all perpetrated by white nationalists with firearms. By analyzing large Twitter datasets in response to the attacks, we were able to render visible associations among actors across religions communities, national identities, and political persuasions. What this project revealed is that if we apply actor-network-theory and data visualization to look at networks created by human/non-human (text, computer, phone, meme, tweet, retweet, hashtag) actors, we can see that knowledge, empathy, and fascination drive communication around mass violence against religious communities.

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