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.

Anthropomorphism and OTA chatbot adoption: a mixed methods study

Abstract: ABSTRACT Anthropomorphizing chatbots can facilitate effective customer interaction. Based on a mixed method, this study explores perceived chatbot anthropomorphism cues and their effects on customers’ chatbot usage intentions (UIs)in the online travel agency context. Findings suggest that (1) social presence cues and emotional message cues are major anthropomorphic cues of interest for customers and enterprises; (2) social presence cues by simply using a human avatar or mentioning the customer’s name might not be sufficient; (3) anthropomorphic emotional message cues are essential in shaping customers’ UIs; and (4) perceived trustworthiness, intelligence, and enjoyment mediate the above effect.

Multilingual Healthcare Chatbot Using Machine Learning

Abstract: The healthcare sector is one of the largest focus areas in the world today. Health problems are becoming increasingly common. India faces a huge challenge in terms of managing rural healthcare. Early diagnosis and treatment of diseases can play an instrumental role. Physical consultation, particularly in the rural areas, is costly and time consuming. The solution is adopting healthcare chatbots. The proposed solution describes a multilingual healthcare chatbot application that can perform disease diagnosis based on user symptoms. It also responds to user queries by calculating sentence similarity by using TF-IDF and Cosine Similarity techniques and choosing the most appropriate response from its knowledge database. The multilingual capabilities of the chatbot system make it highly suitable for use in rural India. The chatbot application currently supports three languages namely English, Hindi and Gujarati. The chatbot application converses with the user using concepts of Natural Language Processing and also supports speech to text and text to speech conversion so that the user can also communicate using voice. Five different Machine Learning algorithms have been analyzed for disease prediction. The Random Forest Classifier produces the best results and gives an accuracy of 98.43%. Thus, it is used as the system’s core classifier.

The Effect of Perceived Similarity in Dominance on Customer Self-Disclosure to Chatbots in Conversational Commerce

Abstract: Recent years have seen increased interest in the application of chatbots for conversational commerce. However, many chatbots are falling short of their expectations because customers are reluctant to disclose personal information to them (e.g., product interest, email address). Drawing on social response theory and similarity-attraction theory, we investigated (1) how a chatbot’s language style influences users’ perceived similarity in dominance (i.e., an important facet of personality) between them and the chatbot and (2) how these perceptions influence their self-disclosure behavior. We conducted an online experiment (N=205) with two chatbots with different language styles (dominant vs. submissive). Our results show that users attribute a dominant personality to a chatbot that uses strong language with frequent assertions, commands, and self-confident statements. Moreover, we find that the interplay of the user’s own dominance and the chatbot’s perceived dominance creates perceptions of similarity. These perceptions of similarity increase users’ degree of self-disclosure via an increased likelihood of accepting the chatbot’s advice. Our study reveals that language style is an important design feature of chatbots and highlights the need to account for the interplay of design features and user characteristics. Furthermore, it also advances our understanding of the impact of design on self-disclosure behavior.

Designing a Chatbot Social Cue Configuration System

Abstract: Social cues (e.g., gender, age) are important design features of chatbots. However, choosing a social cue design is challenging. Although much research has empirically investigated social cues, chatbot engineers have difficulties to access this knowledge. Descriptive knowledge is usually embedded in research articles and difficult to apply as prescriptive knowledge. To address this challenge, we propose a chatbot social cue configuration system that supports chatbot engineers to access descriptive knowledge in order to make justified social cue design decisions (i.e., grounded in empirical research). We derive two design principles that describe how to extract and transform descriptive knowledge into a prescriptive and machine-executable representation. In addition, we evaluate the prototypical instantiations in an exploratory focus group and at two practitioner symposia. Our research addresses a contemporary problem and contributes with a generalizable concept to support researchers as well as practitioners to leverage existing descriptive knowledge in the design of artifacts.

A Psycholinguistic Model of Man-Machine Interactions Based on Needs of Human Personality

Abstract: Fast development of internet services together with a need to automate maintains of internet services in order to reduce expenses force to use some artificial intelligence solutions that are able to interact between a man and a machine Such interactions can be carried out using internet chatbots that are able to communicate with a human in natural language supplemented with voice synthesizers A main drawback of today systems is that they do not recognize nor understand and weakly react to human needs A conversation will satisfy a human if some implemented algorithms will be able to passively recognize and classify human needs and adjust a conversation and reactions to these needs This paper describes a new personality model that can be successfully used by chatbots to achieve this goal The presented personality model figures out words, phrases and sentence constructions that can be recognized in a conversation, describes personality needs and suitable intelligent reactions to these needs in order to provide a human with satisfaction