Combining artificial intelligence and expert content analysis to explore radical views on twitter: Case study on far-right discourse

Ajala, Imène; Feroze, Shanaz; Barachi, May El; Oroumchian, Farhad; Mathew, Sujith Samuel; Yasin, Rand; Lutfi, Saad

doi:10.1016/j.jclepro.2022.132263

Cited by 10 publications

(4 citation statements)

References 14 publications

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“…The qualitatively formed thematic clusters ultimately reflect the tweet topics in the TWLZ. This approach, combining natural language processing and expert content analysis, has previously been employed in other thematic contexts [79], and with this study, the applicability in the education sector will be implemented.…”

Section: Tweet Analysis (Rq3)mentioning

confidence: 99%

From Research to Retweets—Exploring the Role of Educational Twitter (X) Communities in Promoting Science Communication and Evidence-Based Teaching

Déchène,

Lesperance,

Ziernwald

et al. 2024

Education Sciences

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Twitter has evolved from its initial purpose as a microblogging social network to a pivotal platform for science communication. Equally, it has gained significant popularity among teachers who utilize communities like the German #twitterlehrerzimmer (TWLZ; Twitter teachers’ lounge) as a digital professional learning network. (1) Background: To date, no studies examine how science communication is conducted on Twitter specifically tailored to teachers’ needs and whether this facilitates evidence-based teaching. (2) Methods: Answering the three research questions involved a comprehensive mixed methods approach comprising an online teacher survey, utility analysis using Analytical Hierarchy Process (AHP) models, and machine learning-assisted tweet analyses. (3) Results: Teachers implement research findings from the TWLZ in their teaching about twice a month. They prefer interactive tweets with specific content-related, communicative, and interactive tweet features. Science communication in the TWLZ differs from everyday communication but notably emphasizes the relevance of transfer events for educational practice. (4) Conclusions: Findings highlight that dialogue is essential for successful science communication. Practical implications arise from new guidelines on how research findings should be communicated and encourage teachers to reflect on their Twitter usage and attitude toward evidence-based teaching. Recommendations for further research in this emerging field are also discussed.

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Section: Tweet Analysis (Rq3)mentioning

confidence: 99%

From Research to Retweets—Exploring the Role of Educational Twitter (X) Communities in Promoting Science Communication and Evidence-Based Teaching

Déchène,

Lesperance,

Ziernwald

et al. 2024

Education Sciences

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show abstract

“…For example, Bennet and Gough (2013) collected qualitative data from online discussion forums by conducting keyword searches to determine how men discuss their body weight management efforts through TA. In addition, Ajala et al (2022) collected Twitter data using hashtags and classified some of the content as "expert content" related to political science to identify extreme views on social media. This study follows a similar data collection strategy and relies mainly on social media and websites (or traditional media channels that post on the social media).…”

Section: Data Sources and Collectionmentioning

confidence: 99%

Third-country economic consequences of Western sanctions on Russia: a thematic analysis of expert opinions in Azerbaijan

Niftiyev

2023

SEC

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With the beginning of a new phase of military conflict between Russia and Ukraine in 2022, third countries, especially countries of the former Soviet Union (post-Soviet space), are expected to suffer from Western sanctions and Russian countermeasures due to disruption or disruptions in supply chains. The systematization of literary sources on this topic proves that several studies are currently devoted to analysing the impact of international sanctions against Russia on the situation in the Baltic region. At the same time, the issue of the effects of Russian sanctions on the functioning of Azerbaijan in this context has yet to be analyzed. However, close relations between Russia and Azerbaijan and the growing importance of Azerbaijan for European energy security are essential conditions for this case study. This article aims to investigate the economic impact of sanctions on Azerbaijan through a thematic analysis of expert opinions on social media platforms (e.g. Facebook, LinkedIn) and websites dedicated to media coverage of this issue. This study analyzed 134 qualitative sources collected between February and July 2022, of which 84% of the data was in text format, while 16% was in video format. A technical assessment of expert opinion found that international trade, services (such as banking and transport), agriculture, monetary issues (inflation due to rising prices of imported products and the exchange rate) and migrants were the most discussed issues and causes of concern among experts. Significant disruptions in the Russian economy raise severe concerns about Azerbaijan’s fruit and vegetable exports, wheat imports, banking operations, inflation, reduced remittances (from Russia) and labor migration (from Russia to Azerbaijan). This study examines these patterns in light of prior expectations, suggests further research, and theorizes possible reasons for the observed patterns.

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“…Therefore, given these and more challenges, recent advances in Natural Language Processing (NLP) demonstrate strong potential to enhance online discussion by facilitat-ing the discussion process [6,5]. Furthermore, automatically analysing the available information in these discussions can help to identify political concerns of citizens or major points of conflict between users, providing useful insights for decision makers to make more inclusive and representative decisions [1,4]. As the rise of large language models (LLMs) like GPT-4 and ChatGPT accelerates, the question of how to integrate these technologies to enhance meaningful discussions becomes even more pressing.…”

Section: Introductionmentioning

confidence: 99%

Developing and Validating Tools for the Automated Analysis and Enhancement of Online Discussions

Komander,

Cerquides,

Piera

2023

Frontiers in Artificial Intelligence and Applications

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Online discussions play a vital role in today’s society and recent advances in Natural Language Processing (NLP) demonstrate promising potential for analyzing and facilitating them. This paper proposes a comprehensive framework that involves developing NLP tools based on the latest advances in Large Language Models (LLMs), creating and automating measures to assess the quality of discussions, integrating these tools into online discussion platforms, and designing and implementing adequate experiments to evaluate their usefulness. We emphasize the importance of both user feedback and well-designed experiments to assess how the accelerated development of LLMs can contribute to society. By collaborating with various stakeholders in citizen science and deliberative democracy platforms, we seek to integrate our framework in a meaningful manner. Overall, our framework offers a roadmap for leveraging LLMs to enhance online discussions in a responsible and effective way.

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Combining artificial intelligence and expert content analysis to explore radical views on twitter: Case study on far-right discourse

Cited by 10 publications

References 14 publications

From Research to Retweets—Exploring the Role of Educational Twitter (X) Communities in Promoting Science Communication and Evidence-Based Teaching

From Research to Retweets—Exploring the Role of Educational Twitter (X) Communities in Promoting Science Communication and Evidence-Based Teaching

Third-country economic consequences of Western sanctions on Russia: a thematic analysis of expert opinions in Azerbaijan

Developing and Validating Tools for the Automated Analysis and Enhancement of Online Discussions

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