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Chatbot

About: Chatbot is a research topic. Over the lifetime, 2415 publications have been published within this topic receiving 24372 citations. The topic is also known as: IM bot & AI chatbot.


Papers
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Proceedings ArticleDOI
15 Apr 2020
TL;DR: An experimental study to evaluate the usability of a modelling chatbot called SOCIO, comparing it with the on-line tool Creately, and found that SOCIO saved time and reduced communication effort over Creately.
Abstract: Modelling is a fundamental activity in software engineering, which is often performed in collaboration. For this purpose, on-line tools running on the cloud are frequently used. However, recent advances in Natural Language Processing have fostered the emergence of chatbots, which are increasingly used for all sorts of software engineering tasks, including modelling. To evaluate to what extent chatbots are suitable for collaborative modelling, we conducted an experimental study with 54 participants, to evaluate the usability of a modelling chatbot called SOCIO, comparing it with the on-line tool Creately. We employed a within-subjects cross-over design of 2 sequences and 2 periods. Usability was determined by attributes of efficiency, effectiveness, satisfaction and quality of the results. We found that SOCIO saved time and reduced communication effort over Creately. SOCIO satisfied users to a greater extent than Creately, while in effectiveness results were similar. With respect to diagram quality, SOCIO outperformed Creately in terms of precision, while solutions with Creately had better recall and perceived success. However, in terms of accuracy and error scores, both tools were similar.

16 citations

Proceedings ArticleDOI
Yanran Li1, Ke Li1, Hongke Ning1, Xiaoqiang Xia1, Yalong Guo1, Chen Wei1, Jianwei Cui1, Bin Wang1 
11 Jul 2021
TL;DR: The authors leverage counseling strategies and develop an empathetic chatbot to utilize the causal emotion information to gather emotion causes in online environments, and verify the effectiveness of the proposed approach by comparing their chatbot with several SOTA methods using automatic metrics, expert-based human judgements as well as user-based online evaluation.
Abstract: Existing emotion-aware conversational models usually focus on controlling the response contents to align with a specific emotion class, whereas empathy is the ability to understand and concern the feelings and experience of others. Hence, it is critical to learn the causes that evoke the users' emotion for empathetic responding, a.k.a. emotion causes. To gather emotion causes in online environments, we leverage counseling strategies and develop an empathetic chatbot to utilize the causal emotion information. On a real-world online dataset, we verify the effectiveness of the proposed approach by comparing our chatbot with several SOTA methods using automatic metrics, expert-based human judgements as well as user-based online evaluation.

16 citations

01 Aug 2017
TL;DR: It is assumed that raising the freedom of dialogue can stimulate the user's interest in learning and show that the chatbot as an auxiliary system showed a much lower turn success ratio than the independent chatbot system.
Abstract: This paper presents a chatbot for a Dialogue-Based Computer-Assisted second Language Learning (DB-CALL) system. A DB-CALL system normally leads dialogues by asking questions according to given scenarios. User utterances outside the scenarios are normally considered as semantically improper and simply rejected. In this paper, we assume that raising the freedom of dialogue can stimulate the user's interest in learning. For this, a chatbot based on a search engine with a dialogue corpus has been developed to deal with conversations out of the scenarios. We evaluate the chatbot separately in two different cases: as an independent bot and as an auxiliary system. The results showed that, unlike the independent chatbot system, the chatbot as an auxiliary system showed a much lower turn success ratio.

16 citations

Proceedings ArticleDOI
01 Jul 2020
TL;DR: The algorithmic framework for an automatic news chatbot is described and the results of a usability study are presented that shows that news readers using the system successfully engage in multi-turn conversations about specific news stories.
Abstract: This work describes an automatic news chatbot that draws content from a diverse set of news articles and creates conversations with a user about the news Key components of the system include the automatic organization of news articles into topical chatrooms, integration of automatically generated questions into the conversation, and a novel method for choosing which questions to present which avoids repetitive suggestions We describe the algorithmic framework and present the results of a usability study that shows that news readers using the system successfully engage in multi-turn conversations about specific news stories

16 citations

Journal ArticleDOI
TL;DR: This article investigated the impacts of chatbots' technical features on employees' perceptions (namely, chatbot effectiveness and discomfort with using chatbots) in the context of B2B marketing.

16 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023916
20221,413
2021564
2020617
2019528
2018326