Use Of Bots Research Articles

Adopting Third-party Bots for Managing Online Communities

Bots have become critical for managing online communities on platforms, especially to match the increasing technical sophistication of online harms. However, community leaders often adoptthird-party bots, creating room for misalignment in their assumptions, expectations, and understandings (i.e., their technological frames) about them. On platforms where sharing bots can be extremely valuable, how community leaders can revise their frames about bots to more effectively adopt them is unclear. In this work, we conducted a qualitative interview study with 16 community leaders on Discord examining how they adopt third-party bots. We found that participants addressed challenges stemming from uncertainties about a bot's security, reliability, and fit through emergent social ecosystems. Formal and informal opportunities to discuss bots with others across communities enabled participants to revise their technological frames over time, closing gaps in bot-specific skills and knowledge. This social process of learning shifted participants' perspectives of the labor of bot adoption into something that was satisfying and fun, underscoring the value of collaborative and communal approaches to adopting bots. Finally, by shaping participants' mental models of the nature, value, and use of bots, social ecosystems also raise some practical tensions in how they support user creativity and customization in third-party bot use. Together, the social nature of adopting third-party bots in our interviews offers insight into how we can better support the sharing of valuable user-facing tools across online communities.

Generative artificial intelligence in the electoral processes of 2024 in the world: disinformation campaigns and online trolls

The article conducts research and presents some conclusions about the role of generative artificial intelligence in electoral processes. Most of the election campaigns of the heads of state and parliament of the countries of the world involve the use of modern information and communication, digital technologies and artificial intelligence technologies. The use of artificial intelligence in an election campaign can help improve the efficiency and effectiveness of a campaign, but it can also lead to misinformation of the public. Today, destructive attempts to influence people, societies and entire states are no longer new challenges on the Internet, in connection with which outright lies, political propaganda, incitement to hatred, manipulative technologies are firmly rooted in the Internet space and the latest technologies are actively used for this. The use of bots, or automated social media accounts, has greatly facilitated the dissemination of deliberately false information, as well as false rumors and other types of misinformation. However, the bots used earlier in the elections often produced poorly constructed, grammatically incorrect sentences. Now that the creation of large language models (artificial intelligence systems that create text) is becoming more accessible to more people, some researchers fear that automated social media accounts will soon become much more convincing. Disinformation campaigns and online trolls will increasingly use generative AI to spread false information about elections. Thus, new technologies can cause some harm to the social security of society.

Bots as an online communication tool in the political process on the example of the EDC-2023 in Russia

The article presents a brief theoretical overview of the types of bots, the purposes of their use, identification methods, and also examines global political campaigns with the active use of automated systems. Using the example of the 2023 regional election campaign, an empirical study was conducted, the purpose of which is to identify the features of using bot systems in online communication of the authorities represented by candidates and society. The study was conducted on the basis of open data from the VKontakte social network - all publications were selected in which candidates for the election of heads of regions for the period from August 28 to September 10, 2023 were mentioned. A total of 21 regions and 116 candidates were analyzed. The largest number of bots is typical for Moscow, the Moscow Region, the Republic of Khakassia, and the Pskov region. The detection of bots was based on the method of static signs: the same / similar text of the post, the absence of user activity, the absence of real photos, the lack of a personal profile. The data obtained allowed us to formulate conclusions about the use of bots to create a positive and neutral agenda. At the same time, the publications created automatically had zero or low views, which indicates their invisibility to the final audience and inability to influence the formation of public opinion. However, data on the mention of candidates and the presence of their positive image in the social network can be used in the preparation of administrative or analytical reports.

Hate Raids on Twitch: Echoes of the Past, New Modalities, and Implications for Platform Governance

In the summer of 2021, users on the livestreaming platform Twitch were targeted by a wave of "hate raids," a form of attack that overwhelms a streamer's chatroom with hateful messages, often through the use of bots and automation. Using a mixed-methods approach, we combine a quantitative measurement of attacks across the platform with interviews of streamers and third-party bot developers. We present evidence that confirms that some hate raids were highly-targeted, hate-driven attacks, but we also observe another mode of hate raid similar to networked harassment and specific forms of subcultural trolling. We show that the streamers who self-identify as LGBTQ+ and/or Black were disproportionately targeted and that hate raid messages were most commonly rooted in anti-Black racism and antisemitism. We also document how these attacks elicited rapid community responses in both bolstering reactive moderation and developing proactive mitigations for future attacks. We conclude by discussing how platforms can better prepare for attacks and protect at-risk communities while considering the division of labor between community moderators, tool-builders, and platforms.

Search engine manipulation to spread pro-Kremlin propaganda

The Kremlin’s use of bots and trolls to manipulate the recommendation algorithms of social media platforms is well-documented by many journalists and researchers. However pro-Kremlin manipulation of search engine algorithms has rarely been explored. We examine pro-Kremlin attempts to manipulate search engine results by comparing backlink and keyphrase networks of US, European, and Russian think tanks, as well as Kremlin-linked “pseudo” think tanks that target Western audiences. Our evidence suggests that pro-Kremlin pseudo-think tanks are being artificially boosted and co-amplified by a network of low-quality websites that generate millions of backlinks to these target websites. We find that Google’s search algorithm appears to be penalizing Russian and pseudo-think tank domains.

Who Posts Fake News? Authentic and Inauthentic Spreaders of Fabricated News on Facebook and Twitter

ABSTRACT Fake news has become a threat to the stability of electoral processes in the last years, spreading through decentralised and fragmented infrastructures of digital platforms. This study examines the characteristics of digital accounts that published fake news stories on social media in the 2018 Brazilian presidential elections, taking into account the type, relevance and propensity of robotisation of 1073 users. The study shows that fake news stories are disseminated more by personal profiles than by pages, and that most parts of the principal spreaders presented highly relevant performance, the vast majority being Facebook accounts and a reasonable slice of Twitter. The most relevant accounts in the fake news spreading on Facebook and Twitter were classified as: “not bot-like” and “not bot”, while those framed as “bot-like” or “not possible to assert” had 4.7 times less sharing. This research also shows that fake news spreading cannot be explained mainly by the use of bots, especially in elections.

Fake News as the Newest Tool of Manipulation and Disinformation

The purpose of the article is to characterise the features of fake news as a new means of propaganda, disinformation, and manipulation. The research methodology is based on the interdisciplinary integration of methodological tools of a number of approaches, taking into account the principles of objectivity, systematicity, and reliability. The system method has been used to analyse fake news as a complex-structured communication system; as a socio-communicative phenomenon within social networks – functional; as the newest form of rumor – comparative. In addition, the research methodology is based on general scientific methods of analysis, synthesis, generalisation, and systematisation. Scientific novelty consists in improving the scientific conceptualisation of the concept of fake news as a new means of manipulation, disinformation, and propaganda. Conclusions. Fake is false news, invented stories for the purpose of obtaining any benefit (financial, political, or other), the authenticity of which is provided by fabricated media formats: text message, advertisement, photo, video or audio fakes, use of bots, trolls who actively participate in discussions. Types of fakes include outright misinformation, manipulation, propaganda, rumors, memes, alternative facts, "viral" content, pranking, news satire, generators of news, and synthesised media content. Social networks play the biggest role in spreading fake information. Currently, the issues of forming critical thinking skills and information literacy of the population, conducting campaigns to form a strategy against fake news, to prevent the risk of losing trust in democracy and Internet technologies, as well as to resist the manipulation of public opinion, are becoming actualised. Keywords: fake, deepfake, false information, social networks, manipulation, Internet communication.

Digital Authoritarianism in the Middle East: Deception, Disinformation and Social Media

Digital Authoritarianism in the Middle East: Deception, Disinformation and Social Media

Creating Conspiracy Beliefs: How Our Thoughts Are Shaped

Creating Conspiracy Beliefs: How Our Thoughts Are Shaped

‘More Social’ Means ‘More Flawed’: How New Media is Contributing to the Breakdown of Polish Democracy

It is no coincidence that anti-democratic changes in the recent years in Poland occurred alongside the rapid development of social media. Technologically advanced methods of discourse management (e.g., behavioral targeting) have successfully exploited the poor understanding of social media mechanisms among Poles1 (Drzewiecki, 2010) and created a fertile ground for undermining liberal democracy. Social media have endangered public debate by facilitating the spread of hate speech, fake news, deep fakes, trivialization of public discourse, astroturfing,2 and the use of bots for propaganda purposes. It seems that in the young and unstable Polish democracy, the combination of anti-democratic forces and dynamic development of social media poses a unique threat to the development of society.

IMPLEMENTATION OF CHAT-BOTS IN THE HR PRACTICE OF A CONSTRUCTION ENTERPRISE

The article examines the practical aspect of the introduction of chatbots into the company's activities, taking into account its practical activities. Under the conditions of market relations, the responsibility and independence of enterprises in the development and adoption of management decisions to ensure the effectiveness of their activities increases. That is why the search for alternative solutions in the HR practice of a construction company is becoming relevant in today's crisis economy, namely the introduction of chatbots. The article analyzes and presents the main trends of its direction, as well as positive and negative sides. In modern business conditions, the construction sector plays a significant role in the domestic economy. Construction ensures the reproduction of fixed assets in all sectors of the economy, has numerous inter-sectoral connections and a high multiplier effect. More than 50% of the total investment in fixed capital is for the construction of buildings (residential and non-residential) and structures. Therefore, taking into account the analysis of the trends in the development of enterprises, it is determined that the construction industry plays an important role both in the regional economy and in the economy of the country. The sphere of construction is the main link in accelerating the development of other spheres of the national economy, as well as ensuring the appropriate level of people's quality of life. The use of Bots as automatic agents operating in the Internet space are not simple mechanical devices.Their presence indicates the formation of a new reality, in which artificial actors, partially endowed with human-like properties, are integrated into social relations. Therefore, the analysis of bots and their actions in various spheres of life is extremely relevant. In modern business conditions, bots are actively introduced into the field of human resource management, accordingly, the topic of automation and robotization of human resource management processes is at the peak of popularity. Keywords: construction enterprise, chatbot, personnel, profit, HR activity, development, industry, automation tool.

Can bots Support Employees in Lessening Digital Fatigue During e-Work: Research Results

The pandemic situation has obliged organizations to shift all possible tasks to the Internet and to replace on-site work by its remote version. Without a preparation stage, companies were forced to adopt remote working at the individual-level and cloud computing at the organization level simultaneously. As a consequence, the accelerated shift toward digital work forced employees to rapidly learn how to use various ICT tools (which were not necessarily compatible with each other) and how to implement them into a daily routine.The protracted pandemic has led to many employees working from home, especially those doing knowledge-based work, and has often imposed remote work without the on-site option. This has led (and is still leading) to digital fatigue of workers (a phenomenon that negatively affects the performance of both the employee and the organization), the effects of which have already been named and described by scientists. One solution to unburden employees could be by relieving them from everyday, repetitive, and often tedious jobs By delegating these tasks to bots (especially those that may be subject to automation), it will enable employees to deal with more creative and knowledge-based tasks that require attention and do not cause the same level of fatigue and weariness. In this paper, the research question enquires whether there are commonplace digital processes in organizations that can be automated. If yes, then which technologies are used on a regular basis to automate the processes. The conducted literature review helped to distinguish three categories of standard digital processes suitable for automation – Information and Communication Technology (ICT) based processes (written and spoken), Robotic Process Automation (RPA) and processes of searching for specific information. The empirical research was conducted using the CATI questionnaire in 2020 on 400 organizations which use cloud computing for daily routines. The results indicate that the identified processes are indeed subject to automation, and organizations use bots for RPA most (27.5%), and voice chatbots least (3.75%). The use of bots is also shown to be statistically dependent on a company’s scope and size.

(Re)shaping online narratives: when bots promote the message of President Trump during his first impeachment.

Influencing and framing debates on Twitter provides power to shape public opinion. Bots have become essential tools of ‘computational propaganda’ on social media such as Twitter, often contributing to a large fraction of the tweets regarding political events such as elections. Although analyses have been conducted regarding the first impeachment of former president Donald Trump, they have been focused on either a manual examination of relatively few tweets to emphasize rhetoric, or the use of Natural Language Processing (NLP) of a much larger corpus with respect to common metrics such as sentiment. In this paper, we complement existing analyses by examining the role of bots in the first impeachment with respect to three questions as follows. (Q1) Are bots actively involved in the debate? (Q2) Do bots target one political affiliation more than another? (Q3) Which sources are used by bots to support their arguments? Our methods start with collecting over 13M tweets on six key dates, from October 6th 2019 to January 21st 2020. We used machine learning to evaluate the sentiment of the tweets (via BERT) and whether it originates from a bot. We then examined these sentiments with respect to a balanced sample of Democrats and Republicans directly relevant to the impeachment, such as House Speaker Nancy Pelosi, senator Mitch McConnell, and (then former Vice President) Joe Biden. The content of posts from bots was further analyzed with respect to the sources used (with bias ratings from AllSides and Ad Fontes) and themes. Our first finding is that bots have played a significant role in contributing to the overall negative tone of the debate (Q1). Bots were targeting Democrats more than Republicans (Q2), as evidenced both by a difference in ratio (bots had more negative-to-positive tweets on Democrats than Republicans) and in composition (use of derogatory nicknames). Finally, the sources provided by bots were almost twice as likely to be from the right than the left, with a noticeable use of hyper-partisan right and most extreme right sources (Q3). Bots were thus purposely used to promote a misleading version of events. Overall, this suggests an intentional use of bots as part of a strategy, thus providing further confirmation that computational propaganda is involved in defining political events in the United States. As any empirical analysis, our work has several limitations. For example, Trump’s rhetoric on Twitter has previously been characterized by an overly negative tone, thus tweets detected as negative may be echoing his message rather than acting against him. Previous works show that this possibility is limited, and its existence would only strengthen our conclusions. As our analysis is based on NLP, we focus on processing a large volume of tweets rather than manually reading all of them, thus future studies may complement our approach by using qualitative methods to assess the specific arguments used by bots.

Rising Above Misinformation and Deepfakes

Misinformation can be rapidly spread in cyberspace. It thrives in the social media landscape as well as news platforms. Misinformation can readily gain momentum in the race to influence people or intentionally deceive. With the use of bots, misinformation can be easily shared, especially in environments like Twitter and Facebook. While, some measures are taken to stop the spread of misinformation, threats like Deepfakes are posing a higher challenge. Deepfakes provide a means to generate fake digital content in order to impersonate a person. With the use of audio, images and videos, artificial intelligence is used to depict the speech and actions of people. Deepfakes are typically made of presidents or influential businessmen such as Donald Trump and Mark Zuckerberg. Deep Fakes can be very realistic and convincing as this form of synthetic media is raising concerns about its possible misuse. The effects of Deepfakes are to spread disinformation, confuse users or create influence. This can lead to further effects like political factions, blackmail, harassment and extortion. Deepfakes could lead to a distrust in digital content as many may feel that anything we see is actually just a manipulation. Deepfakes has arisen as a new generation of misinformation through the manipulation of digital media in order to create realistic videos. This paper looks at the governing, communal and technical issues relating to Deepfakes. At the technical level, the use of audio and text analysis used to create Deepfake videos is advancing at a rapid pace which has also made its affordability and accessibility easier. An evaluation of the threats stemming from Deepfakes reveals that there are various mental, monetary and group dynamics involved. In this paper, the various types of threats emanating from Deepfakes is discussed. This paper also looks at five factors in the field of Deepfakes that should be taken into consideration (Technical Source Dissemination Victim Viewers). The paper discussed these five factors in order to help identify measures to help curb the spread of Deepfakes. A combination of these measures can help limit the spread of Deepfakes and support mitigation of the threat. Due to prominence and power that digital media has, it is imperative that this threat not be overlooked. The paper provides a holistic approach to understanding the risk and impact of Deepfakes, as well measures to help mitigate abuse thereof.

Why Botter: How Pro-Government Bots Fight Opposition in Russia

There is abundant anecdotal evidence that nondemocratic regimes are harnessing new digital technologies known as social media bots to facilitate policy goals. However, few previous attempts have been made to systematically analyze the use of bots that are aimed at a domestic audience in autocratic regimes. We develop two alternative theoretical frameworks for predicting the use of pro-regime bots: one which focuses on bot deployment in response to offline protest and the other in response to online protest. We then test the empirical implications of these frameworks with an original collection of Twitter data generated by Russian pro-government bots. We find that the online opposition activities produce stronger reactions from bots than offline protests. Our results provide a lower bound on the effects of bots on the Russian Twittersphere and highlight the importance of bot detection for the study of political communication on social media in nondemocratic regimes.

Боти у соціальних медіа: реалії та перспективи для українських передвиборних кампаній

The use of social media is an important component of political campaigning. But at the same time, it can be a source of some risks, such as bots’ functioning. The article demonstrates that the latter poses significant problems for the Ukrainian political sphere. Since bots are most often used to spread disinformation (or fakes), distort public opinion, create the illusion of massive voter support for certain political forces (or their representatives), make it difficult for political competitors to communicate with supporters, etc. The article covers some examples of this phenomenon in pre-election campaigns, both in parliamentary and local elections in Ukraine. This is an additional confirmation of the prevalence of bots at various levels of competition between political forces for election victory. It has been determined that the joint work of the governments of countries, intergovernmental bodies, companies that own social media, and relevant scientists are necessary to find an effective solution to the problem of this destructive influence. The most common signs of bots were also outlined (the presence of a fake photo in the account; the absence of personal information, a valid name, friends (or a small number of them – in case this information is made public); anomalous activity manifested in the distribution of other people’s content, publication of the same type content (texts, photos, videos, graphics or drawings, etc.), and prospects for use in future election campaigns. Social media users’ behavior is also analyzed in the article. Another direction in the development and use of bots, which does not foresee negative consequences, but on the contrary allows optimizing and structuring work, speeding up communication with voters, exercising more effective control over compliance with election legislation, and quickly reducing the scale of violations is highlighted in the article. Examples of their application by some political parties in the elections to the Verkhovna Rada of Ukraine are included.

Culture of Socio-political Internet Discussion with the Use of Bots

Culture of Socio-political Internet Discussion with the Use of Bots

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.

Lots of bots or maybe nots: A process for detecting bots in social media research

The use of bot messaging, that being artificially created messages, has increased since 2010. While not all bots are bad, many have been used to share extreme and divisive views on a range of topics, from policy discussion to brand electronic word of mouth. The issue with bot messaging and its prevalence is that it can affect researchers’ understanding of a topic. For example, if 25% of a dataset is fabricated, decision-making may result in a loss of profit or poor policy formation. To counteract the use of bots, this research note offers a framework to alleviate the potentially destructive nature of bot data and ensure the cleaning of data is thorough and beneficial to decision-making based on social media commentary. The framework is a four-step process, which includes thematic, automated, and characteristic identification stages. We provide three case studies to demonstrate the approach and conclude by providing key practical implications.

Use of bot and content flags to limit the spread of misinformation among social networks: a behavior and attitude survey.

The COVID-19 infodemic is driven partially by Twitter bots. Flagging bot accounts and the misinformation they share could provide one strategy for preventing the spread of false information online. This article reports on an experiment (N = 299) conducted with participants in the USA to see whether flagging tweets as coming from bot accounts and as containing misinformation can lower participants’ self-reported engagement and attitudes about the tweets. This experiment also showed participants tweets that aligned with their previously held beliefs to determine how flags affect their overall opinions. Results showed that flagging tweets lowered participants’ attitudes about them, though this effect was less pronounced in participants who frequently used social media or consumed more news, especially from Facebook or Fox News. Some participants also changed their opinions after seeing the flagged tweets. The results suggest that social media companies can flag suspicious or inaccurate content as a way to fight misinformation. Flagging could be built into future automated fact-checking systems and other misinformation abatement strategies of the social network analysis and mining community.