A New Chatbot for Customer Service on Social Media

By Anbang Xu, Zhe Liu, Yufan Guo, Vibha Sinha, Rama Akkiraju. International Conference on Human Factors in Computing Systems, 2017

536 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems

View Paper: https://www.semanticscholar.org/paper/90bd099501147609165971b27b5514a2b9c2a7e7

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Citations in the corpus

Are We There Yet? - A Systematic Literature Review on Chatbots in Education (2021, background): “Outside of education, typical applications of chatbots are in customer service (Xu et al., 2017), counseling of hospital patients (Vaidyam et al.”
Interacting with educational chatbots: A systematic review (2022, background): “…human conversations and thus automate services and reduce effort, chatbots are increasingly becoming popular in several domains, including healthcare (Oh et al., 2017), consumer services (Xu et al., 2017), education (Anghelescu & Nicolaescu, 2018), and academic advising (Alkhoori et al., 2020).”
Why People Use Chatbots (2017, background): “In particular, chatbots are seen as a promising alternative to traditional customer service [4].”
Efficient Intent Detection with Dual Sentence Encoders (2020, background): “…conversation in order to solve a particular task with well-deﬁned semantics, such as booking restau-rants, hotels and ﬂights (Hemphill et al., 1990; Williams, 2012; El Asri et al., 2017), providing tourist information (Budzianowski et al., 2018), or automating customer support (Xu et al., 2017).”
Artificial Intelligence (AI) Student Assistants in the Classroom: Designing Chatbots to Support Student Success (2022, background): “Chatbots’ interactive, cost-effective nature has led to a growth in their popularity and applications in multiple industries, primarily for customer service (Xu et al., 2017; Johannsen & Leist, 2018; Behera et al., 2021; Chuah & Kabilan, 2021; Kushwaha and Kar, 2021; Nguyen et al., 2021).”
Artificial intelligence in the creative industries: a review (2020, background): “Similarly, chatbots and other types of virtual assistants are used for marketing, customer service, finding specific content and information gathering [252].”
BigBlueBot: teaching strategies for successful human-agent interactions (2019, methodology): “We developed a 6-item Likert scale to measure empathy 2 motivated by the description given by Xu et al. [44]: “The bot should give individualized attention to a user and make them feel valued.””
What Makes Users Trust a Chatbot for Customer Service? An Exploratory Interview Study (2018, background): “Intelligent automation of customer service may allow for accessible and efficient support while keeping costs at an acceptable level [23].”
An Overview of Chatbot Technology (2020, background): “According to a study, social media user requests on chatbots for customer service are emotional and informational, with the ﬁrst category rate being more than 40% and with users not intending to take speciﬁc information [22].”
Text Style Transfer: A Review and Experiment Evaluation (2020, background): “The research and development of chatbots, i.e., intelligent dialogue systems that are able to engage in conversations with humans, has been one of the longest-running goals in artificial intelligence [1, 80, 95].”
I Lead, You Help but Only with Enough Details: Understanding User Experience of Co-Creation with Artificial Intelligence (2018, background): “Many HCI researchers have conducted user studies on various AI interfaces [28, 42, 58], and the concept of algorithmic experience has been suggested as a new perspective from which to view the user experience of AI interfaces [41].”