I hate you! Disinhibition with virtual partners

By Antonella De Angeli, Sheryl Brahnam. 2008

109 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Social Psychology, Sociology and Political Science, Human-Computer Interaction

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Jason Aaron Edward Weston
2. Y-Lan Boureau
3. Emily Dinan
4. Minlie Huang
5. Eric Michael Smith
6. Kurt Shuster
7. Da Ju
8. Jing Xu

In Social Psychology

1. Y-Lan Boureau
2. Lebogang Wame Molefi
3. Verena Rieser
4. Jing Xu
5. Amanda Cercas Curry
6. Emily Dinan
7. Mun Yong Yi
8. Hyojin Chin

In Sociology and Political Science

1. Lebogang Wame Molefi
2. Verena Rieser
3. Amanda Cercas Curry
4. Mun Yong Yi
5. Hyojin Chin
6. Jason Aaron Edward Weston
7. Xiaoyan Zhu
8. Gavin Abercrombie

In Human-Computer Interaction

1. Lebogang Wame Molefi
2. Jason Aaron Edward Weston
3. Verena Rieser
4. Gavin Abercrombie
5. Mun Yong Yi
6. Dirk Hovy
7. A. S. Bergman
8. Jing Xu

Citations in the corpus

• Anticipating Safety Issues in E2E Conversational AI: Framework and Tooling (2021, background): “Non-adversarial unsafe setting: Past research suggests that one in ten human-bot conversations may contain abusive behavior on the part of the human (De Angeli & Carpenter, 2005; De Angeli & Brahnam, 2008).”
• Recipes for Safety in Open-domain Chatbots (2020, background): “Other past studies (De Angeli and Carpenter, 2005; De Angeli and Brahnam, 2008) suggest that one in ten human-bot conversations may contain instances of the human demonstrating unprovoked abusive behavior towards the chatbot.”
• Bot-Adversarial Dialogue for Safe Conversational Agents (2021, background): “De Angeli and Carpenter (2005); De Angeli and Brahnam (2008) suggest that one in ten human-bot conversations may contain instances of the human demonstrating unprovoked abusive behavior towards the chatbot.”
• SafetyKit: First Aid for Measuring Safety in Open-domain Conversational Systems (2022, background): “This can for example include abusive user behavior, which according to past research affects one in ten human-bot conversations (De Angeli and Carpenter, 2005; De Angeli and Brahnam, 2008).”
• Interacting with educational chatbots: A systematic review (2022, background): “Such chatbots can learn from previous user input in similar contexts (De Angeli & Brahnam, 2008).”
• Should an Agent Be Ignoring It?: A Study of Verbal Abuse Types and Conversational Agents' Response Styles (2019, methodology): “However, there is growing evidence that, if not mitigated this type of behavior, can transfer to real-life social relationships [3].”
• On the Safety of Conversational Models: Taxonomy, Dataset, and Benchmark (2021, background): “Dialogue safety requires open-domain chatbots to deal appropriately with various scenarios including aggressiveness (De Angeli et al., 2005; De Angeli and Brahnam, 2008), ha-rassment (Curry and Rieser, 2018), and sensitive topics (Xu et al., 2020), etc.”
• Empathy Is All You Need: How a Conversational Agent Should Respond to Verbal Abuse (2020, background): “Moreover, most prior research examined text-based interactions [10, 11, 18, 22].”
• A Crowd-based Evaluation of Abuse Response Strategies in Conversational Agents (2019, background): “, 2018), and how to handle verbal abuse from the user’s side (Cercas Curry and Rieser, 2018; Angeli and Brahnam, 2008; Angeli and Carpenter, 2006; Brahnam, 2005).”