Role Of Bots Research Articles

Mapping automatic social media information disorder. The role of bots and AI in spreading misleading information in society.

This paper presents an analysis on information disorder in social media platforms. The study employed methods such as Natural Language Processing, Topic Modeling, and Knowledge Graph building to gain new insights into the phenomenon of fake news and its impact on critical thinking and knowledge management. The analysis focused on four research questions: 1) the distribution of misinformation, disinformation, and malinformation across different platforms; 2) recurring themes in fake news and their visibility; 3) the role of artificial intelligence as an authoritative and/or spreader agent; and 4) strategies for combating information disorder. The role of AI was highlighted, both as a tool for fact-checking and building truthiness identification bots, and as a potential amplifier of false narratives. Strategies proposed for combating information disorder include improving digital literacy skills and promoting critical thinking among social media users.

"Nip it in the Bud": Moderation Strategies in Open Source Software Projects and the Role of Bots

Much of our modern digital infrastructure relies critically upon open sourced software. The communities responsible for building this cyberinfrastructure require maintenance and moderation, which is often supported by volunteer efforts. Moderation, as a non-technical form of labor, is a necessary but often overlooked task that maintainers undertake to sustain the community around an OSS project. This study examines the various structures and norms that support community moderation, describes the strategies moderators use to mitigate conflicts, and assesses how bots can play a role in assisting these processes. We interviewed 14 practitioners to uncover existing moderation practices and ways that automation can provide assistance. Our main contributions include a characterization of moderated content in OSS projects, moderation techniques, as well as perceptions of and recommendations for improving the automation of moderation tasks. We hope that these findings will inform the implementation of more effective moderation practices in open source communities.

Law and Artificial Intelligence: Possibilities and Regulations on the Road to the Consummation of the Digital Verdict

Aim: The continuous growing influence of technologies based on artificial intelligence will continue to have an increasingly strong impact on various fields of society, which is evident in the generation of a great expectation in continuous evolution that revolutionises many activities, including those of the legal sector.
 
 Methodology: That is why this paper aims to shed light on those aspects of artificial intelligence in the legal field that are not very clear and on some of the most relevant implications that, despite not being well known, will have a considerable impact on society at various levels, such as the role of bots in law firms, algorithms to assist in the treatment of cases and dilemmas such as whether non-professional users can trust the decision(s) that such tools would recommend, among others.
 
 Results: It also examines the ethical criteria linked to the application and its development.
 
 Conclusion: It concludes with a critical exposition from an academic perspective, without neglecting the aspect of public access to artificial intelligence and how to bring together a process of globalisation of the regulatory framework of these technologies.
 
 Originality/Value: this study highlities technologies based on artificial intelligence.

The role of bots in spreading conspiracies: Case study of discourse about earthquakes on Twitter

In this paper, we identified seven most widely spread conspiracy discourses about earthquakes. These conspiracy discourses link earthquakes to military activities like secret nuclear bomb testing, God's Providence like the punishment of humans for their sins, space activities like aliens visiting our planet, the US secret weather control program HAARP, tests of the Large Hadron Collider, fracking projects, and freemasonic plots. Following the major earthquake in Indonesia at the end of November 2022, we extracted data from Twitter by keywords using the Hoaxy tool for tracking the spread of information on Twitter. Applying the Bot Sentinel tool, we also got data on the sentiment of the users. The divine and military discourses dominated the conspiracy discussion, followed by the discussions about extraction and HAARP. Though there were more human-like accounts than bot-like accounts, we found a positive correlation between the frequency of tweets on the conspiracy discourses and the bot scores of the accounts, which suggests that bot-like accounts were tweeting more than human-like accounts. It was also found that normal accounts tweeted more than toxic accounts, and there was a positive relationship between the bot score and the toxicity level of an account. It suggests that bot-like accounts were involved more in disruptive activities than human-like accounts.

The role of bots in U.S. Real estate development online communication

Planners and policymakers have been quick to open electronic channels of participation to inform decision-making processes due to the low cost and high potential engagement. This has created an opportunity for subversive groups to amplify their voice, and therefore influence, in land development and planning processes using automated social media accounts. While scholars have begun to examine how social media platforms such as Facebook and Twitter have been used to manipulate political discourse, no research has considered the potential damage that such manipulation can and does cause in the local planning context. This study examines the role and potential risk of automated social media accounts in the participatory planning process through an empirical investigation of 21 real estate development projects in the U.S. Using a machine learning model to assess 41,191 relevant Tweets, we found that at least 10% and upwards of 50% of Tweets concerning the various real estate development projects were generated by bots. Automated tweets included critical, neutral, and supportive content demonstrating that social bots represent a range of interests. Planning and public policy professionals will need to develop, apply, and be aware of bot-detection tools and actively promote and build trust through their own digital channels to ensure accurate information is disseminated.

The Role of Bots in the Disinformation Process in Brazilian Politics between 2014 and 2018

Abstract This paper presents the participation of bots in the process of disinformation in the Brazilian political/electoral scenario between 2014 and 2018. The justification for this research was the growth of ideological polarization and the emergence of hate speech linked to political positioning that culminated in a massive campaign of disinformation, evidenced by fake news and other forms of manipulation. In this research multiple case studies were used referring to three moments: the 2014 elections, the 2016 impeachment and the 2018 election. We found studies investigating these events, and they were used as data sources for analysis of the conjuncture and the interpretation of these facts in a chronological perspective pointed toward the role of bots and the results of such actions. It has been observed that the use of bots has occurred since 2014; however, they were only engaged in propagating false content from 2015. The automation of the messages was sophisticated between 2014 and 2018, when bots ceased to be players who replicated posts indiscriminately (spam) to become users’ catalysts with the intention of creating or expanding new bubbles of disinformation. Finally, we observed that the same botnet active in Brazil was also involved in electoral processes around the world, making Brazil simply one more piece in this grand network of disinformation where who is involved and what their purpose might be is not known.

Even in Sweden?1: Misinformation and elections in the new media landscape

Abstract The Swedish national parliamentary election of 2018 took place amidst considerable concern over the role of misinformation. This paper examines the role of digital media during the election against the background of the Swedish media system. It focuses on the role of bots and how they supported the Sweden Democrats, whose agenda was also promoted by anti-immigrant alternative news websites. This article reports on a study of Twitter that used computational techniques to distinguish bots from genuine accounts across hashtags related to the election and Swedish politics (such as #valet2018). I examine which parties are supported and criticised by bots and by genuine accounts, and discuss the content of the tweets. In this article, I place bots in the context of broader debates about the role of digital media in politics and argue that misinformation and alternative news websites will demand continued future vigilance.

(Un)Trendy Japan: Twitter bots and the 2017 Japanese general election

Abstract Social networking services (SNSs) can significantly impact public life during important political events. Thus, it comes as no surprise that different political actors try to exploit these online platforms for their benefit. Bots constitute a popular tool on SNSs that appears to be able to shape public opinion and disrupt political processes. However, the role of bots during political events in a non-Western context remains largely under-studied. This article addresses the question of the involvement of Twitter bots during electoral campaigns in Japan. In our study, we collected Twitter data over a fourteen-day period in October 2017 using a set of hashtags related to the 2017 Japanese general election. Our dataset includes 905,215 tweets, 665,400 of which were unique tweets. Using a supervised machine learning approach, we first built a custom ensemble classification model for bot detection based on user profile features, with an area under curve (AUC) for the test set of 0.998. Second, in applying our model, we estimate that the impact of Twitter bots in Japan was minor overall. In comparison with similar studies conducted during elections in the US and the UK, the deployment of Twitter bots involved in the 2017 Japanese general election seems to be significantly lower. Finally, given our results on the level of bots on Twitter during the 2017 Japanese general election, we provide various possible explanations for their underuse within a broader socio-political context.

Hateful People or Hateful Bots?

Arabic Twitter space is crawling with bots that fuel political feuds, spread misinformation, and proliferate sectarian rhetoric. While efforts have long existed to analyze and detect English bots, Arabic bot detection and characterization remains largely understudied. In this work, we contribute new insights into the role of bots in spreading religious hatred on Arabic Twitter and introduce a novel regression model that can accurately identify Arabic language bots. Our assessment shows that existing tools that are highly accurate in detecting English bots don't perform as well on Arabic bots. We identify the possible reasons for this poor performance, perform a thorough analysis of linguistic, content, behavioral and network features, and report on the most informative features that distinguish Arabic bots from humans as well as the differences between Arabic and English bots. Our results mark an important step toward understanding the behavior of malicious bots on Arabic Twitter and pave the way for a more effective Arabic bot detection tools.

Examining Emergent Communities and Social Bots Within the Polarized Online Vaccination Debate in Twitter

Many states in the United States allow a “belief exemption” for measles, mumps, and rubella (MMR) vaccines. People’s opinion on whether or not to take the vaccine can have direct consequences in public health. Social media has been one of the dominant communication channels for people to express their opinions of vaccination. Despite governmental organizations’ efforts of disseminating information of vaccination benefits, anti-vaccine sentiment is still gaining momentum. Studies have shown that bots on social media (i.e., social bots) can influence opinion trends by posting a substantial number of automated messages. The research presented here investigates the communication patterns of anti- and pro-vaccine users and the role of bots in Twitter by studying a retweet network related to MMR vaccine after the 2015 California Disneyland measles outbreak. We first classified the users into anti-vaccination, neutral to vaccination, and pro-vaccination groups using supervised machine learning. We discovered that pro- and anti-vaccine users retweet predominantly from their own opinion group. In addition, our bot analysis discovers that 1.45% of the corpus users were identified as likely bots which produced 4.59% of all tweets within our dataset. We further found that bots display hyper-social tendencies by initiating retweets at higher frequencies with users within the same opinion group. The article concludes that highly clustered anti-vaccine Twitter users make it difficult for health organizations to penetrate and counter opinionated information while social bots may be deepening this trend. We believe that these findings can be useful in developing strategies for health communication of vaccination.