Design and Development of Conversational Chatbot for Covid-19 using NLP: an AI application

Singh, Shivani; Kaur, Manmeet; Tanwar, Pooman; Sharma, Shweta

doi:10.1109/iccmc53470.2022.9753893

Cited by 9 publications

(3 citation statements)

References 16 publications

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“…Time horizon [28,34,40,41,45,[47][48][49][50][51]59] 11 (20) Short term [31,33,36,39,[42][43][44]46,54,[56][57][58]60,63,64,[66][67][68][69][70][71][72][73][74][75][76] 26 (46) Medium term [35,38] 2 (4) Long term [10,[22][23][24][25][26][27]29,30,32,37,52,…”

Section: Study Values N (%) Design Dimension and Design Characteristicmentioning

confidence: 99%

“…Role [10,[22][23][24]26,[29][30][31][32][33][34]38,39,41,43,47,50,51,[55][56][57][58]63,64,[66][67][68][69][70][71][72][73]75,76] 33 (59) Expert [25,27,[35][36][37]40,45,53,54,[59][60][61][62]65,72] 15 (27) Facilitator [28,42,…”

Section: Study Values N (%) Design Dimension and Design Characteristicmentioning

confidence: 99%

“…Communication modality [22,23,25,26,29,30,[32][33][34][35][36][37][38][39][40][41]43,[45][46][47][48]51,54,55,57,[60][61][62][63][64][65][66]68,69,71,72,74,75] 38 (68) Text only [10,24,27,28,42,44,49,50,52,53,56,59,67,70,…”

Section: Study Values N (%) Design Dimension and Design Characteristicsmentioning

confidence: 99%

See 2 more Smart Citations

General Characteristics and Design Taxonomy of Chatbots for COVID-19: Systematic Review

Lim¹,

Custodio²,

Sunga³

et al. 2024

J Med Internet Res

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Background A conversational agent powered by artificial intelligence, commonly known as a chatbot, is one of the most recent innovations used to provide information and services during the COVID-19 pandemic. However, the multitude of conversational agents explicitly designed during the COVID-19 pandemic calls for characterization and analysis using rigorous technological frameworks and extensive systematic reviews. Objective This study aims to describe the general characteristics of COVID-19 chatbots and examine their system designs using a modified adapted design taxonomy framework. Methods We conducted a systematic review of the general characteristics and design taxonomy of COVID-19 chatbots, with 56 studies included in the final analysis. This review followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to select papers published between March 2020 and April 2022 from various databases and search engines. Results Results showed that most studies on COVID-19 chatbot design and development worldwide are implemented in Asia and Europe. Most chatbots are also accessible on websites, internet messaging apps, and Android devices. The COVID-19 chatbots are further classified according to their temporal profiles, appearance, intelligence, interaction, and context for system design trends. From the temporal profile perspective, almost half of the COVID-19 chatbots interact with users for several weeks for >1 time and can remember information from previous user interactions. From the appearance perspective, most COVID-19 chatbots assume the expert role, are task oriented, and have no visual or avatar representation. From the intelligence perspective, almost half of the COVID-19 chatbots are artificially intelligent and can respond to textual inputs and a set of rules. In addition, more than half of these chatbots operate on a structured flow and do not portray any socioemotional behavior. Most chatbots can also process external data and broadcast resources. Regarding their interaction with users, most COVID-19 chatbots are adaptive, can communicate through text, can react to user input, are not gamified, and do not require additional human support. From the context perspective, all COVID-19 chatbots are goal oriented, although most fall under the health care application domain and are designed to provide information to the user. Conclusions The conceptualization, development, implementation, and use of COVID-19 chatbots emerged to mitigate the effects of a global pandemic in societies worldwide. This study summarized the current system design trends of COVID-19 chatbots based on 5 design perspectives, which may help developers conveniently choose a future-proof chatbot archetype that will meet the needs of the public in the face of growing demand for a better pandemic response.

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Section: Study Values N (%) Design Dimension and Design Characteristicmentioning

confidence: 99%

Section: Study Values N (%) Design Dimension and Design Characteristicmentioning

confidence: 99%

See 1 more Smart Citation

General Characteristics and Design Taxonomy of Chatbots for COVID-19: Systematic Review

Lim¹,

Custodio²,

Sunga³

et al. 2024

J Med Internet Res

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show abstract

Recommendation system for animal healthcare virtual conversational AI-assistant Chabot

Tembhare,

Thakur

2024

AIP Conference Proceedings

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A Medical Diagnosis and Treatment Recommendation Chatbot using MLP

Ogirala,

Tallapaneni,

Chalamcharla

et al. 2023

2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC)

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Design and Development of Conversational Chatbot for Covid-19 using NLP: an AI application

Cited by 9 publications

References 16 publications

General Characteristics and Design Taxonomy of Chatbots for COVID-19: Systematic Review

General Characteristics and Design Taxonomy of Chatbots for COVID-19: Systematic Review

Recommendation system for animal healthcare virtual conversational AI-assistant Chabot

A Medical Diagnosis and Treatment Recommendation Chatbot using MLP

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