research-article

Future directions for chatbot research: an interdisciplinary research agenda

Authors:

Asbjørn Følstad,

Effie Lai-Chong Law,

Petter Bae Brandtzaeg,

Symeon Papadopoulos,

Patrick McAllister,

Carolin Ischen,

Raphael Meyer von Wolff,

Sebastian Hobert,

Ewa LugerAuthors Info & Claims

Computing, Volume 103, Issue 12

Pages 2915 - 2942

https://doi.org/10.1007/s00607-021-01016-7

Published: 01 December 2021 Publication History

Abstract

Chatbots are increasingly becoming important gateways to digital services and information—taken up within domains such as customer service, health, education, and work support. However, there is only limited knowledge concerning the impact of chatbots at the individual, group, and societal level. Furthermore, a number of challenges remain to be resolved before the potential of chatbots can be fully realized. In response, chatbots have emerged as a substantial research area in recent years. To help advance knowledge in this emerging research area, we propose a research agenda in the form of future directions and challenges to be addressed by chatbot research. This proposal consolidates years of discussions at the CONVERSATIONS workshop series on chatbot research. Following a deliberative research analysis process among the workshop participants, we explore future directions within six topics of interest: (a) users and implications, (b) user experience and design, (c) frameworks and platforms, (d) chatbots for collaboration, (e) democratizing chatbots, and (f) ethics and privacy. For each of these topics, we provide a brief overview of the state of the art, discuss key research challenges, and suggest promising directions for future research. The six topics are detailed with a 5-year perspective in mind and are to be considered items of an interdisciplinary research agenda produced collaboratively by avid researchers in the field.

References

[1]

Adam M, Wessel M, and Benlian A AI-based chatbots in customer service and their effects on user compliance Electron Markets 2020

[2]

Adiwardana D, Luong MT, So DR, Hall J, Fiedel N, Thoppilan R, Le QV (2020) Towards a human-like open-domain chatbot. arXiv preprint. arXiv:2001.09977

[3]

Amershi S, Weld D, Vorvoreanu M, Fourney A, Nushi B, Collisson P, Teevan J (2019) Guidelines for human–AI interaction. In: Proceedings of the CHI 2019 (paper no. 3). ACM, New York

[4]

Araujo T Living up to the chatbot hype: the influence of anthropomorphic design cues and communicative agency framing on conversational agent and company perceptions Comput Hum Behav 2018 85 183-189

[5]

Araujo T Conversational agent research toolkit: an alternative for creating and managing chatbots for experimental research Comput Commun Res 2020 2 1 35-51

[6]

Ashktorab Z, Jain M, Liao QV, Weisz JD (2019) Resilient chatbots: repair strategy preferences for conversational breakdowns. In: Proceedings of CHI 2019 (paper no. 254). ACM, New York

[7]

Baez M, Daniel F, Casati F (2019) Conversational web interaction: proposal of a dialog-based natural language interaction paradigm for the Web. In: Chatbot research and design. Third international workshop, CONVERSATIONS. Springer, Cham, pp 94–11

[8]

Bavaresco R, Silveira D, Reis E, Barbosa J, Righi R, Costa C, Moreira C (2020) Conversational agents in business: a systematic literature review and future research directions. Comput Sci Rev 36:100239.

[9]

Bender EM, Gebru T, McMillan-Major A, Mitchell M (2021) On the dangers of stochastic parrots: can language models be too big? In: Proceedings of the 2021 ACM conference on fairness, accountability, and transparency. ACM, New York, pp 610–623

[10]

Bickmore T and Picard RW Establishing and maintaining long-term human–computer relationships ACM Trans Comput Hum Interact 2005 12 2 293-327

[11]

Bittner E, Shoury O (2019) Designing automated facilitation for design thinking: a chatbot for supporting teams in the empathy map method. In: Proceedings of the 52nd Hawaii international conference on system sciences. Scholar Space, Honolulu, pp 227–236

[12]

Bobrow DG, Kaplan RM, Kay M, Norman DA, Thompson H, and Winograd T GUS, a frame-driven dialog system Artif Intell 1977 8 2 155-173

[13]

Bott N, Wexler S, Drury L, Pollak C, Wang V, Scher K, and Narducci S A protocol-driven, bedside digital conversational agent to support nurse teams and mitigate risks of hospitalization in older adults: case control pre-post study J Med Internet Res 2019 21 10 e13440

[14]

Brandtzaeg PB, Følstad A (2017) Why people use chatbots. In: Proceeedings of the international conference on internet science—INSCI 2017. Springer, Cham, pp 377–392

[15]

Breazeal C Toward sociable robots Robot Auton Syst 2003 42 3–4 167-175

[16]

Brown TB, Mann B, Ryder N, Subbiah M, Kaplan J, Dhariwal P, Amodei D (2020) Language models are few-shot learners. arXiv preprint. arXiv:2005.14165

[17]

Candello H, Pinhanez C, Pichiliani M, Cavalin P, Figueiredo F, Vasconcelos M, Carmo DH (2019) The effect of audiences on the user experience with conversational interfaces in physical spaces. In: Proceedings of CHI 2019 (paper no. 90). ACM, New York

[18]

Cassell J, Bickmore T, Billinghurst M, Campbell L, Chang K, Vilhjálmsson H, Yan H (1999) Embodiment in conversational interfaces: Rea. In: Proceedings of CHI ‘99. ACM, New York, pp 520–527

[19]

Catania F, Di Nardo N, Garzotto F, Occhiuto D (2019) Emoty: an emotionally sensitive conversational agent for people with neurodevelopmental disorders. In Proceedings of the 52nd Hawaii international conference on system sciences. Scholar Space, Honolulu, pp 2014–2023

[20]

Chen H, Liu X, Yin D, and Tang J A survey on dialogue systems: recent advances and new frontiers ACM SIGKDD Explor Newsl 2017 19 2 25-35

[21]

Chung H, Iorga M, Voas J, and Lee S Alexa, can I trust you? Computer 2017 50 9 100-104

[22]

Ciechanowski L, Przegalinska A, Magnuski M, and Gloor P In the shades of the uncanny valley: an experimental study of human–chatbot interaction Future Gener Comput Syst 2019 92 539-548

[23]

Corkrey R and Parkinson L Interactive voice response: review of studies 1989–2000 Behav Res Methods Instruments Comput 2002 34 3 342-353

[24]

Cranor LF (2008) A framework for reasoning about the human in the loop. In :UPSec’08: Proceedings of the 1st conference on usability, psychology, and security. USENIX Association, Berkeley

[25]

Dale R The return of the chatbots Nat Lang Eng 2016 22 5 811-817

[26]

Daniel G, Cabot J, Deruelle L, and Derras M Xatkit: a multimodal low-code chatbot development framework IEEE Access 2020 8 15332-15346

[27]

DeVault D, Artstein R, Benn G, Dey T, Fast E, Gainer A, Morency LP (2014) SimSensei Kiosk: a virtual human interviewer for healthcare decision support. In Proceedings of the 2014 international conference on autonomous agents and multi-agent systems, pp 1061–1068

[28]

Deriu J, Rodrigo A, Otegi A, Echegoyen G, Rosset S, Agirre E, and Cieliebak M Survey on evaluation methods for dialogue systems Artif Intell Rev 2021 54 755-810

[29]

Devlin J, Chang MW, Lee K, Toutanova K (2018) Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint, arXiv:1810.04805

[30]

European Commission (2019) Ethics guidelines for trustworthy AI. Retrieved from: https://digital-strategy.ec.europa.eu/en/library/ethics-guidelines-trustworthy-ai

[31]

Farooq U and Grudin J Human–computer integration Interactions 2016 23 6 26-32

[32]

Feine J, Gnewuch U, Morana S, and Maedche A A taxonomy of social cues for conversational agents Int J Hum Comput Stud 2019 132 138-161

[33]

Feine J, Gnewuch U, Morana S, Maedche A (2019b) Gender bias in chatbot design. In: Chatbot research and design. Third international workshop CONVERSATIONS 2019. Springer, Cham, pp 79–93

[34]

Ferrara E What types of COVID-19 conspiracies are populated by Twitter bots? First Monday 2020

[35]

Fitzpatrick KK, Darcy A, Vierhile M (2017) Delivering cognitive behavior therapy to young adults with symptoms of depression and anxiety using a fully automated conversational agent (Woebot): a randomized controlled trial. JMIR Mental Health 4(2):e19

[36]

Floridi L, Chiriatti M (2020) GPT-3: Its nature, scope, limits, and consequences. Mind Mach 30(4):681–694

[37]

Frey CB and Osborne MA The future of employment: How susceptible are jobs to computerisation? Technol Forecast Soc Chang 2017 114 254-280

[38]

Følstad A and Brandtzæg PB Chatbots and the new world of HCI Interactions 2017 24 4 38-42

[39]

Følstad A, Brandtzaeg PB (2020) Users’ experiences with chatbots: findings from a questionnaire study. Quality User Exp.

[40]

Følstad A, Brandtzaeg PB, Feltwell T, Law ELC, Tscheligi M, Luger E (2018) Chatbots for social good. In: Extended abstracts of the 2018 CHI conference on human factors in computing systems (paper no. SIG06). ACM, New York

[41]

Følstad A, Araujo T, Papadopoulos S, Law EL-C, Luger E, Goodwin M, Brandtzaeg PB (eds) (2020) Chatbot research and design 4th international workshop, CONVERSATIONS 2020. Springer, Cham

[42]

Go E and Sundar SS Humanizing chatbots: the effects of visual, identity and conversational cues on humanness perceptions Comput Hum Behav 2019 97 304-316

[43]

Goel AK, Polepeddi L (2016) Jill Watson: A virtual teaching assistant for online education. Georgia Institute of Technology. Retrieved from https://smartech.gatech.edu/handle/1853/59104

[44]

Gorwa R and Guilbeault D Unpacking the social media bot: a typology to guide research and policy Policy Internet 2020 12 2 225-248

[45]

Grudin J, Jacques R (2019) Chatbots, humbots, and the quest for artificial general intelligence. In: Proceedings of CHI 2019 (paper no. 209). ACM, New York

[46]

Guzman AL and Lewis SC Artificial intelligence and communication: a human–machine communication research agenda New Media Soc 2019 22 1 70-86

[47]

Hagendorff T The ethics of AI ethics: An evaluation of guidelines Mind Mach 2020 30 1 99-120

[48]

Hall E Conversational Design 2018 New York A Book Apart

[49]

Hao K (2020) We read the paper that forced Timnit Gebru out of Google. Here’s what it says. MIT Technology Review. Retrieved from https://www.technologyreview.com/2020/12/04/1013294/google-ai-ethics-research-paper-forced-out-timnit-gebru/

[50]

Harms JG, Kucherbaev P, Bozzon A, and Houben GJ Approaches for dialog management in conversational agents IEEE Internet Comput 2018 23 2 13-22

[51]

Harwell D (2018) The accent gap. The Washington Post. Retrieved from https://www.washingtonpost.com/graphics/2018/business/alexa-does-not-understand-your-accent/

[52]

Ho A, Hancock J, and Miner AS Psychological, relational, and emotional effects of self-disclosure after conversations with a chatbot J Commun 2018 68 4 712-733

[53]

Hobert S, Berens F (2019) Small talk conversations and the long-term use of chatbots in educational settings–experiences from a field study. In: Chatbot research and design. Third international workshop CONVERSATIONS 2019. Springer, Cham, pp 260–272

[54]

Hobert S, Meyer von Wolff, R (2019) Say hello to your new automated tutor—a structured literature review on pedagogical conversational agents. In: Proceedings of the 14th international conference on Wirtschaftsinformatik. Association for Information Systems, pp.301–313

[55]

Hoffman G, Breazeal C (2004) Collaboration in human–robot teams. In: AIAA 1st intelligent systems technical conference.

[56]

Hsieh T, Chaudhury B, Cross ES (2020) Human–robot cooperation in prisoner dilemma games: people behave more reciprocally than prosocially toward robots. In: Companion of the 2020 ACM/IEEE international conference on human–robot interaction. ACM, New York, pp 257–259

[57]

Jain M, Kumar P, Kota R, Patel SN (2018) Evaluating and informing the design of chatbots. In: Proceedings of the 2018 designing interactive systems conference. ACM, New York, pp 895–906

[58]

McTear MF Spoken dialogue technology: enabling the conversational user interface ACM Comput Surv (CSUR) 2002 34 1 90-169

[59]

Jokinen K and McTear M Spoken dialogue systems. Synthesis lectures on human language technologies 2009 Williston Morgan & Claypool Publishers

[60]

Jovanovic M, Baez M, and Casati F Chatbots as conversational healthcare services IEEE Internet Comput 2020

[61]

Jurafsky D, Martin JH (2020) Dialogue systems and chatbots. In: Speech and language processing. Draft of December 30, 2020. https://web.stanford.edu/~jurafsky/slp3/24.pdf

[62]

Kim S, Lee J, Gweon G (2019) Comparing data from chatbot and web surveys: effects of platform and conversational style on survey response quality. In: Proceedings of CHI 2019 (paper no. 86). ACM, New York

[63]

Kocaballi AB, Laranjo L, and Coiera E Understanding and measuring user experience in conversational interfaces Interact Comput 2019 31 2 192-207

[64]

Kopp S, Gesellensetter L, Krämer NC, Wachsmuth I (2005) A conversational agent as museum guide–design and evaluation of a real-world application. In: International workshop on intelligent virtual agents. Springer, Heidelberg, pp 329–343

[65]

Kretzschmar K, Tyroll H, Pavarini G, Manzini A, Singh I (2019) Can your phone be your therapist? Young people’s ethical perspectives on the use of fully automated conversational agents (chatbots) in mental health support. Biomed Inform Insights.

[66]

Kvale K, Sell OA, Hodnebrog S, Følstad A (2019) Improving conversations: lessons learnt from manual analysis of chatbot dialogues. In: Chatbot research and design. Third international workshop CONVERSATIONS 2019. Springer, Cham, pp 187–200

[67]

Laban G, George J, Morrison V, and Cross ES Tell me more! Assessing interactions with social robots from speech Paladyn Journal of Behavioral Robotics 2021 12 1 136-159

[68]

Laban G, Araujo T (2019) Working together with conversational agents: the relationship of perceived cooperation with service performance evaluations. In: Chatbot research and design. Third international workshop CONVERSATIONS 2019. Springer, Cham, pp 215–228

[69]

Laban G, Araujo T (2020) The effect of personalization techniques in users’ perceptions of conversational recommender system. In: IVA ’20: Proceedings of the 20th ACM international conference on intelligent virtual agents (paper no. 34). ACM, New York

[70]

Latour B Reassembling the Social - An introduction to actor-network-theory 2005 Oxford, UK Oxford University Press

[71]

Lee S and Choi J Enhancing user experience with conversational agent for movie recommendation: effects of self-disclosure and reciprocity Int J Hum Comput Stud 2017 103 95-105

[72]

Lester J, Branting K, and Mott B Singh MP Conversational agents The Practical Handbook of Internet Computing 2004 Boca Raton Chapman & Hall/CRC

[73]

Liao QV, Geyer W, Muller M, and Khazaen Y Conversational interfaces for information search Understanding and improving information search 2020 Cham Springer 267-287

[74]

Liao QV, Mas-ud Hussain M, Chandar P, Davis M, Khazaeni Y, Crasso MP, Geyer W (2018) All work and no play? In Proceedings of CHI 2018 (paper no. 3). ACM,New York

[75]

Luger E, Sellen A (2016) “Like having a really bad PA”—the gulf between user expectation and experience of conversational agents. In: Proceedings of CHI 2016. ACM, New York, pp 5286–5297

[76]

McAfee A and Brynjolfsson E Machine, platform, crowd: harnessing our digital future 2017 New York W.W. Norton & Company

[77]

McTear M Conversational AI: Dialogue Systems, Conversational Agents, and Chatbots 2021 Williston Morgan & Claypool

[78]

Meyer von Wolff R, Hobert S, Masuch K, and Schumann M Chatbots at digital workplaces - A grounded-theory approach for surveying application areas and objectives Pac Asia J Assoc Inf Syst 2020 12 2 64-102

[79]

Moore RJ and Arar R Conversational UX design: a practitioner’s guide to the natural conversation framework 2019 Williston Morgan & Claypool

[80]

Nordheim CB, Følstad A, and Bjørkli CA An initial model of trust in chatbots for customer service—findings from a questionnaire study Interact Comput 2019 31 3 317-335

[81]

Ntoutsi E, Fafalios P, Gadiraju U, Iosifidis V, Nejdl W, Vidal ME, Ruggieri S, Turini F, Papadopoulos S, Krasanakis E, and Kompatsiaris I Bias in data-driven artificial intelligence systems—an introductory survey Wiley Interdiscipl Rev Data Min Knowl Discov 2020 10 3 e1356

[82]

Oh CS, Bailenson JN, and Welch GF A systematic review of social presence: definition, antecedents, and implications Front Robot AI 2018 5 114

[83]

Paikens P, Znotiņš A, Bārzdiņš G (2020) Human-in-the-loop conversation agent for customer service. In: Proceedings of the 25th international conference on applications of natural language to information systems, NLDB 2020. Springer, Cham, pp 277–284

[84]

Pérez JQ, Daradoumis T, and Puig JMM Rediscovering the use of chatbots in education: a systematic literature review Comput Appl Eng Educ 2020 28 6 1549-1565

[85]

Perski O, Crane D, Beard E, and Brown J Does the addition of a supportive chatbot promote user engagement with a smoking cessation app? An experimental study Digital Health 2019 5 2055207619880676

[86]

Piccolo LS, Mensio M, Alani H (2018) Chasing the chatbots. In Internet Science. INSCI 2018 international workshops. Springer, Cham, pp 157–169

[87]

Porcheron M, Fischer JE, Reeves S, Sharples S (2018) Voice interfaces in everyday life. In: Proceedings of CHI 2018 (paper no. 640). ACM,New York

[88]

Press G (2019) AI Stats News: 62 % of US Consumers like using chatbots to interact with businesses. Forbes. Retrieved from https://www.forbes.com/sites/gilpress/2019/10/25/ai-stats-news-us-consumers-interest-in-using-chatbots-to-interact-with-businesses-rise-to-62/

[89]

Rodríguez-Gil L, García-Zubia J, Orduña P, Villar-Martinez A, and López-De-Ipiña D New approach for conversational agent definition by non-programmers: a visual domain-specific language IEEE Access 2019 7 5262-5276

[90]

Roller S, Dinan E, Goyal N, Ju D, Williamson M, Liu Y, Boureau YL (2020) Recipes for building an open-domain chatbot. arXiv preprint. arXiv:2004.13637

[91]

Ruane E, Birhane A, Ventresque A (2019) Conversational AI: social and ethical considerations. In: Proceedings for the 27th AIAI Irish conference on artificial intelligence and cognitive science—AICS 2019, pp 104–115. CEUR Workshop Proceedings, Vol-2563. http://ceur-ws.org/Vol-2563/

[92]

Rubin VL, Chen Y, and Thorimbert LM Artificially intelligent conversational agents in libraries Library Hi Tech 2010 28 4 496-522

[93]

Salem M, Kopp S, Wachsmuth I, Rohlfing K, and Joublin F Generation and evaluation of communicative robot gesture Int J Social Robot 2012 4 2 201-217

[94]

Schaake M (2021). The European commission’s artificial intelligence act. Policy Brief, Stanford HAI. Retrieved from https://hai.stanford.edu/sites/default/files/2021-06/HAI_Issue-Brief_The-European-Commissions-Artificial-Intelligence-Act.pdf

[95]

Schuller BW Speech emotion recognition: two decades in a nutshell, benchmarks, and ongoing trends Commun ACM 2018 61 5 90-99

[96]

Seering J, Luria M, Ye C, Kaufman G, Hammer J (2020) It takes a village: integrating an adaptive chatbot into an online gaming community. In: Proceedings of CHI 2020 (paper no. 579). ACM,New York

[97]

Shevat A Designing bots: creating conversational experiences 2017 Boston O’Reilly Media

[98]

Shum HY, He XD, and Li D From Eliza to XiaoIce: challenges and opportunities with social chatbots Front Inf Technol Electron Eng 2018 19 1 10-26

[99]

Strubell E, Ganesh A, McCallum A (2019) Energy and policy considerations for deep learning in NLP. arXiv preprint, arXiv:1906.02243

[100]

Sundar SS Rise of machine agency: a framework for studying the psychology of Human–AI Interaction (HAII) J Comput Mediat Commun 2020 25 1 74-88

[101]

Suresh H, Guttag JV (2019) A framework for understanding unintended consequences of machine learning. arXiv preprint, arXiv:1901.10002

[102]

Syvänen S, Valentini C (2020) Conversational agents in online organization–stakeholder interactions: a state-of-the-art analysis and implications for further research. J Commun Manag 339–362

[103]

Ta V, Griffith C, Boatfield C, Wang X, Civitello M, Bader H, Loggarakis A (2020) User experiences of social support from companion chatbots in everyday contexts: thematic analysis. J Med Internet Res 22(3):e16235

[104]

Toxtli C, Monroy-Hernández A, Cranshaw J (2018) Understanding chatbot-mediated task management. In: Proceedings of CHI 2018 (paper no. 58). ACM,New York

[105]

Vaidyam AN, Wisniewski H, Halamka JD, Kashavan MS, and Torous JB Chatbots and conversational agents in mental health: a review of the psychiatric landscape Can J Psychiatry 2019 64 7 456-464

[106]

Van der Goot MJ, Pilgrim T (2019) Exploring age differences in motivations for and acceptance of chatbot communication in a customer service context. In: Chatbot research and design. Third international workshop CONVERSATIONS 2019. Springer, Cham, pp 173–186

[107]

Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Kaiser Ł, Polosukhin I (2017) Attention is all you need. In: Conference on neural information processing systems—NIPS 2017, pp 5998–6008

[108]

Vaziri M, Mandel L, Shinnar A, Siméon J, Hirzel M (2017) Generating chat bots from web API specifications. In: Proceedings of the 2017 ACM SIGPLAN international symposium on new ideas, new Pparadigm, and reflections on programming and software. ACM, New York, pp 44–57

[109]

Vinyals O, Le Q (2015) A neural conversational model. arXiv preprint, arXiv:1506.05869

[110]

Väänänen K, Hiltunen A, Varsaluoma J, Pietilä I (2019) CivicBots–Chatbots for supporting youth in societal participation. In: Chatbot research and design. Third international workshop CONVERSATIONS 2019. Springer, Cham, pp 143–157

[111]

Wallace R (2003) The elements of AIML style. Alice AI Foundation, 139

[112]

Weizenbaum J Contextual understanding by computers Commun ACM 1967 10 8 474-480

[113]

Wolf T, Debut L, Sanh V, Chaumond J, Delangue C, Moi A, Cistac P, Rault T, Louf R, Funtowicz M, Brew J (2019) HuggingFace’s transformers: state-of-the-art natural language processing. arXiv preprint, arxiv:1910.03771

[114]

Xu A, Liu Z, Guo Y, Sinha V, Akkiraju R (2017) A new chatbot for customer service on social media. In: Proceedings of CHI 2017. ACM, New York, pp 3506–3510

[115]

Yaghoub-Zadeh-Fard MA, Zamanirad S, Benatallah B, Casati F (2020) REST2Bot: bridging the gap between bot platforms and REST APIs. In: Companion proceedings of the web conference 2020. ACM, New York, pp 245–248

[116]

Yang Q, Steinfeld A, Rosé C, Zimmerman J (2020) Re-examining whether, why, and how Human-AI Interaction is uniquely difficult to design. In: Proceedings of CHI 2020 (paper no. 174). ACM,New York

[117]

Zamora J (2017) I’m sorry, Dave, I’m afraid I can’t do that: Chatbot perception and expectations. In: Proceedings of the 5th international conference on human agent Interaction. ACM,New York,pp 253–260

[118]

Zarouali B, Van den Broeck E, Walrave M, and Poels K Predicting consumer responses to a chatbot on Facebook Cyberpsychol Behav Soc Netw 2018 21 8 491-497

[119]

Zierau N, Engel C, Söllner M, Leimeister JM (2020) Trust in smart personal assistants: A systematic literature review and development of a research agenda. In: Proceedings of the 15th international conference on Wirtschaftsinformatik—WI2020. Association for Information Systems,pp 99–11

[120]

Zou J and Schiebinger L AI can be sexist and racist—it’s time to make it fair Nature 2018 559 324-326

Cited By

Braggaar AHe LDe Wit J(2024)Our Dialogue System Sucks - but Luckily we are at the Top of the Leaderboard!: A Discussion on Current Practices in NLP EvaluationProceedings of the 6th ACM Conference on Conversational User Interfaces10.1145/3640794.3665889(1-5)Online publication date: 8-Jul-2024
https://dl.acm.org/doi/10.1145/3640794.3665889
Dregger ASeifermann MOberweis A(2024)Language Cues for Expressing Artificial Personality: A Systematic Literature Review for Conversational AgentsProceedings of the 6th ACM Conference on Conversational User Interfaces10.1145/3640794.3665559(1-17)Online publication date: 8-Jul-2024
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Index Terms

Future directions for chatbot research: an interdisciplinary research agenda
1. Human-centered computing
  1. Collaborative and social computing
    1. Collaborative and social computing theory, concepts and paradigms
  2. Human computer interaction (HCI)
2. Social and professional topics

Index terms have been assigned to the content through auto-classification.

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cover image Computing

Computing Volume 103, Issue 12

Dec 2021

275 pages

ISSN:0010-485X

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© The Author(s) 2021.

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Published: 01 December 2021

Accepted: 15 September 2021

Received: 03 September 2020

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Cited By

Braggaar AHe LDe Wit J(2024)Our Dialogue System Sucks - but Luckily we are at the Top of the Leaderboard!: A Discussion on Current Practices in NLP EvaluationProceedings of the 6th ACM Conference on Conversational User Interfaces10.1145/3640794.3665889(1-5)Online publication date: 8-Jul-2024
https://dl.acm.org/doi/10.1145/3640794.3665889
Dregger ASeifermann MOberweis A(2024)Language Cues for Expressing Artificial Personality: A Systematic Literature Review for Conversational AgentsProceedings of the 6th ACM Conference on Conversational User Interfaces10.1145/3640794.3665559(1-17)Online publication date: 8-Jul-2024
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