Unraveling the use of disinformation hashtags by social bots during the Covid-19 pandemic: a networks analysis and community detection (Preprint) DOI
Víctor Suárez-Lledó, Esther Ortega-Martin, Jesús Carretero-Bravo

et al.

Published: June 16, 2023

BACKGROUND During the COVID-19 pandemic, social media platforms have been a venue for exchange of messages, including those related to fake news. There are also accounts programmed disseminate and amplify specific which can affect individual decision-making present new challenges public health. OBJECTIVE This paper aims analyze how bots use hashtags compared human users on topics misinformation during outbreak Covid-19 pandemic. METHODS We selected tweets infodemics such as vaccines, hydroxychloroquine, military, conspiracy, laboratory, Bill Gates, 5G, UV. built network based co-occurrence classified their source. Using analysis community detection algorithms, we identified that tend appear together in messages. For each topic, extracted most relevant subtopic communities, groups interconnected hashtags. RESULTS The distribution nonbots these communities was uneven, with some sets being more common among or nonbots. Hashtags Trump Qanon movements were bots, anti-Asian sentiments identified. In subcommunities populated by case group #billgates, #pandemic, #china common. CONCLUSIONS certain varies depending source, used different purposes. Understanding patterns may help address spread health networks.

Language: Английский

Bad robot? The benevolent use of automated software and social bots by influencers in the #antivaxx discourse on Twitter DOI Creative Commons
Antonia Egli, Theo Lynn, Pierangelo Rosati

et al.

Online Information Review, Journal Year: 2025, Volume and Issue: 49(8), P. 44 - 61

Published: Jan. 29, 2025

Purpose Automated social media messaging tactics can undermine trust in health institutions and public advice. As such, we examine automated software programs (ASPs) bots the Twitter anti-vaccine discourse before after release of COVID-19 vaccines. Design/methodology/approach We compare two datasets comprising user accounts associated English-language tweets featuring keywords “#antivaxx” or “anti-vaxx.” The first dataset, from 2018 (pre-COVID vaccine), includes 3,154 6,380 tweets. second comprises 327,067 545,268 published during 12 months following December 1, 2020 (post-COVID vaccine). Using Information Laundering Theory (ILT), were examined manually through analytics machine learning to identify activity, visibility, verification status, vaccine position, ASP bot technology use. Findings post-COVID dataset showed an increase highly probable (31.09%) accounts. However, both dominated by pro-vaccine accounts; most active (59%) visible (50%) classified as pro-vaccine. Originality/value This research is behaviors prevalence mostly benevolent suggests a potential overstatement threat posed using ASPs technologies. By highlighting intermediaries that disseminate pro- content, extend ILT identifying variant offering insights into “pathways” generating mainstream information.

Language: Английский

Citations

0
Conceptualizing the evolving nature of computational propaganda: a systematic literature review DOI Creative Commons
Hassan M. H. Mustafa, Markus Luczak–Roesch, David Johnstone

et al.

Annals of the International Communication Association, Journal Year: 2025, Volume and Issue: unknown

Published: March 14, 2025

Abstract Since the 2016 U.S. election and U.K. Brexit campaign, computational propaganda has become an important research topic in communication, political social science. Recently, it clearer that doesn’t start from a clean slate is not precisely bound to single issues or campaigns. Instead, needs be looked at as complex phenomenon global environment of co-evolving events, emerging technologies, policies legal frameworks, dynamics. Here, we review literature on this perspective theorize evolving longitudinal nature campaigns through lens relational Our conceptual contribution forms basis for new kind empirical aware interdependencies, feedback cycles structural conditions are elusive when focusing individual short time frames.

Language: Английский

Citations

0
Social bots shape public issue networks in China’s dual-carbon agenda: a network analysis using MRQAP DOI Creative Commons
Han Lin, Menghan Zhang, Qi Xue

et al.

Humanities and Social Sciences Communications, Journal Year: 2025, Volume and Issue: 12(1)

Published: March 26, 2025

Language: Английский

Citations

0
Who Leads? Who Follows? Exploring Agenda Setting by Media, Social Bots and Public in the Discussion of the 2022 South Korean Presidential Election DOI Creative Commons
Menghan Zhang, Qi Xue,

Xinyan Liu

et al.

SAGE Open, Journal Year: 2024, Volume and Issue: 14(2)

Published: April 1, 2024

Social media not only changes the traditional communication environment but also brings new to agenda-setting. The main body of agenda-setting has shifted from politicians, political parties and grassroots people. With increasing use social bots in public opinion manipulation election interference, whether they can participate or influence become an urgent concern. So far, there been less literature focusing on engagement for bots. This paper studies discussion content South Korean presidential election, determines participation bots, explores connection between agenda, bot agenda perspective setting. study finds that while agendas media, are same, their relevant. In addition, is timely ahead time order appears public.

Language: Английский

Citations

3
Rise of social bots: The impact of social bots on public opinion dynamics in public health emergencies from an information ecology perspective DOI
Han Luo, Xiao Meng, Yifei Zhao

et al.

Telematics and Informatics, Journal Year: 2023, Volume and Issue: 85, P. 102051 - 102051

Published: Sept. 6, 2023

Language: Английский

Citations

8
Social Media Data in Urban Design and Landscape Research: A Comprehensive Literature Review DOI Creative Commons
Chenghao Yang, Tongtong Liu

Land, Journal Year: 2022, Volume and Issue: 11(10), P. 1796 - 1796

Published: Oct. 14, 2022

Social media data have been widely used in natural sciences and social the past 5 years, benefiting from rapid development of deep learning frameworks Web 2.0. Its advantages gradually emerged urban design, planning, landscape architecture sustainable tourism, other disciplines. This study aims to obtain an overview design research through literature reviews bibliometric visualization as a comprehensive review article. The dataset consists 1220 articles works SSCI, SCIE, A&HCI, based on Science core collection, respectively. progress main directions location-based media, text mining, image vision are introduced. Moreover, we introduce Citespace, computer-network-based visualization, discuss timeline trends, hot burst keywords, with high co-citation scores Citespace. Citespace tool facilitates is outline future trends research. shows that framework has great potential for emotional analysis, classification, object detection, segmentation, expression classification data. intersection text, images, metadata provides attractive opportunities well.

Language: Английский

Citations

10
Theory and practice of agenda setting: understanding media, bot, and public agendas in the South Korean presidential election DOI
Menghan Zhang, Ze Chen,

Xinyan Liu

et al.

Asian Journal of Communication, Journal Year: 2023, Volume and Issue: 34(1), P. 24 - 56

Published: Dec. 4, 2023

Social media not only changes the traditional communication environment, but also introduces new modifications to agenda setting. With increasing use of social bots in public opinion manipulation and political election interference, whether they can participate or influence setting has become an urgent concern. Currently, there is limited literature focusing on engagement agenda-setting for This paper examines content discussion related South Korean presidential election, identifies presence bots, explores relationships between agenda, bot from perspective The study found that although primary agendas media, are identical, interconnected. Furthermore, does precede terms timeliness, chronological order observed public.

Language: Английский

Citations

5
Unraveling the use of disinformation hashtags by social bots during the Covid-19 pandemic: a networks analysis and community detection (Preprint) DOI Creative Commons
Víctor Suárez-Lledó, Esther Ortega-Martin, Jesús Carretero-Bravo

et al.

JMIR Infodemiology, Journal Year: 2024, Volume and Issue: 5, P. e50021 - e50021

Published: May 15, 2024

Background During the COVID-19 pandemic, social media platforms have been a venue for exchange of messages, including those related to fake news. There are also accounts programmed disseminate and amplify specific which can affect individual decision-making present new challenges public health. Objective This study aimed analyze how bots use hashtags compared human users on topics misinformation during outbreak pandemic. Methods We selected posts infodemics such as vaccines, hydroxychloroquine, military, conspiracy, laboratory, Bill Gates, 5G, UV. built network based co-occurrence classified their source. Using analysis community detection algorithms, we identified that tend appear together in messages. For each topic, extracted most relevant subtopic communities, groups interconnected hashtags. Results The distribution nonbots these communities was uneven, with some sets being more common among or nonbots. Hashtags Trump QAnon movements were bots, anti-Asian sentiments identified. In subcommunities populated by case group #billgates, #pandemic, #china common. Conclusions certain varies depending source, used different purposes. Understanding patterns may help address spread health networks.

Language: Английский

Citations

1
Fine-Tuned Understanding: Enhancing Social Bot Detection With Transformer-Based Classification DOI Creative Commons
Amine Sallah, El Arbi Abdellaoui Alaoui, Saïd Agoujil

et al.

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 118250 - 118269

Published: Jan. 1, 2024

In recent years, the proliferation of online communication platforms and social media has given rise to a new wave challenges, including rapid spread malicious bots. These bots, often programmed impersonate human users, can infiltrate communities, disseminate misinformation, engage in various activities detrimental integrity digital discourse. It is becoming more difficult discern text produced by deep neural networks from that created humans. Transformer-based Pre-trained Language Models (PLMs) have recently shown excellent results challenges involving natural language understanding (NLU). The suggested method employ an approach detect bots at tweet level utilizing content fine-tuning PLMs, reduce current threat. Building on developments BERT (Bidirectional Encoder Representations Transformers) GPT-3, model employs embedding approach. This offers high-quality representation enhance efficacy detection. addition, Feedforward Neural Network (FNN) was used top PLMs for final classification. experimentally evaluated using Twitter bot dataset. strategy tested test data came same distribution as their training set. methodology this paper involves preprocessing data, generating contextual embeddings designing classification learns differentiate between users Experiments were carried out adopting advanced construct encoding create potential input vector variants. By employing models, we achieve significant improvements detection F1-score (93%) compared traditional methods such Word2Vec Global Vectors Word Representation (Glove). Accuracy ranging 3% 24% baselines achieved. capability GPT-4, Large Model (LLM), interpreting bot-generated examined research. Additionally, explainable artificial intelligence (XAI) utilized alongside transformer-based models detecting media, enhancing transparency reliability these models.

Language: Английский

Citations

1
Who Leads? Who Follows? Exploring Agenda Setting by Media, Social Bots and Public in the Discussion of 2022 South Korea Presidential Election DOI Creative Commons
Menghan Zhang, Ze Chen,

Xinyan Liu

et al.

Research Square (Research Square), Journal Year: 2023, Volume and Issue: unknown

Published: June 9, 2023

Abstract Social media not only changes the traditional communication environment, but also brings new to agenda setting. The main body of setting has shifted from politicians, political parties and grassroots people. With increasing use social bots in public opinion manipulation election interference, whether they can participate or influence become an urgent concern. So far, there is less literature focusing on engagement agenda-setting for bots. This paper studies discussion content South Korean presidential election, determines participation bots, explores connection between agenda, bot perspective study found that while agendas media, are same, their relevant. In addition, timely ahead time order appears public.

Language: Английский

Citations

1