Is that social bot behaving unethically?

Salge, Carolina; Berente, Nicholas

doi:10.1145/3126492

Cited by 44 publications

(12 citation statements)

References 2 publications

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“…In [24], for instance, the authors investigate how to handle race-talks with a chatbot from a socio-technical perspective. AIbased applications require a wider and deeper discussion on ethical aspects, as initially addressed in [23].…”

Section: Towards Trustfulnessmentioning

confidence: 99%

Chasing the Chatbots

2019

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Section: Towards Trustfulnessmentioning

confidence: 99%

Chasing the Chatbots

2019

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“…In the misinformation related literature, social bots on Twitter are typically associated with having unethical behaviour, being misinformation spreaders [4,12], or content polluters [10,15]. They are not yet seen as a possible agent active in this battle to restrain misinformation spread, nor connected with a conversational agent.…”

Section: Social Bots Designmentioning

confidence: 99%

“…To this end, we introduce a set of two Twitter agents that, in complementary ways, approach Twitter users that have shared verified misinformation, and invite them to follow and interact with a conversational agent that explains the credibility assessment of tweets or news. The first agent is a social bot, as defined in [12] computer algorithms that can share content and connect with users on social media; the second is a conversational agent that, for the moment, verifies whether pieces of news or tweets have already been fact-checked and briefly explains the assessment. As an ongoing research, the conversational agent is evolving to provide deeper explanations of credibility indicators used on fact-checking.…”

Section: Introductionmentioning

confidence: 99%

Agents for Fighting Misinformation Spread on Twitter: Design Challenges

Piccolo

Blackwood

Farrell

et al. 2021

CUI 2021 - 3rd Conference on Conversational User Interfaces

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Containing misinformation spread on social media has been acknowledged as a great socio-technical challenge in the last years.Despite advances, practical and timely solutions to properly communicate verified (mis)information to social media users are an evidenced need. We introduce a multi-agent approach to bridge Twitter users with fact-checked information. First, a social bot, which nudges users sharing verified misinformation, and a conversational agent that verifies if there is a reputable fact-check available and explains existing assessments in natural language. Both agents share the same requirements of evoking trust and being perceived by Twitter users as an opportunity to build their media literacy. To this end, two preliminary human-centred studies are presented, the first one looking for an adequate identity for the bot, and the second for understanding preferences for credibility indicators when explaining the assessment of misinformation. The results indicate what this design research should pursue to create agents that are consistent in their presentation, friendly, engaging, and credible.CCS Concepts: • Human-centered computing → Natural language interfaces.

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“…To date, propaganda has begun to rise exponentially and the global effect has risen by 150% for the past two years according to the Computational Propaganda Research Project (COMPROP) [6]- [8]. The social bots that reside in social media are also believed to be one of the major factors that contributed to the propaganda dispersion in 2017, where approximately 23 million social bots were found in Twitter accounts [9]. The spread of propaganda has not only brought about disruption in global politics but has also caused cyber-hate, riots, threats, and even numerous instances of violence.…”

Section: Introductionmentioning

confidence: 99%

Socio-Technical Mitigation Effort to Combat Cyber Propaganda: A Systematic Literature Mapping

et al. 2020

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This systematic mapping literature aims to identify current research and directions for future studies in terms of combating cyber propaganda in the social media, which is used by both human effort and technological approaches (socio-technical) for mitigation. Out of 5176 retrieved articles, only 98 of them were selected for primary studies; classified based on research artifacts, mitigation effort, and the social media platforms involved in the research. The search was conducted using selected databases and applying selection criteria set for this research. Through the analysis, important research trends were identified based on human effort and technological approaches in mitigating and combating the cyber-propaganda issues. The authors also identified various mitigation socio-technical approaches such as identification, detection, image recognition, prediction, truth discovery and comprehension of rumours flow. The study also highlights areas for further improvements, to complement the performances of existing techniques. Besides, the study provides a brief review of cyber propaganda detection using classification techniques. Hence, it has set forth applicable research focus on the areas dealing with the mitigation of risk borne by cyber propaganda in the social media. INDEX TERMS Systematic mapping review, social media, cyber propaganda, mitigation, human effort, socio-technical approaches.

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Is that social bot behaving unethically?

Abstract: A procedure for reflection and discourse on the behavior of bots in the context of law, deception, and societal norms.

Cited by 44 publications

References 2 publications

Chasing the Chatbots

Chasing the Chatbots

Agents for Fighting Misinformation Spread on Twitter: Design Challenges

Socio-Technical Mitigation Effort to Combat Cyber Propaganda: A Systematic Literature Mapping

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