Linguistic Differences in Real Conversations: Human to Human vs Human to Chatbot
Abstract
This study investigates how students communicate in writing when they know that
their conversational partner is a human being in comparison to how they communicate when
they know their partner is a chatbot. The participants are upper secondary students of English.
The investigation took place in a school in Sweden where English is taught as a foreign
language. The students wrote to their peers through Instant Messaging (IM) and to the chatbot
‘Mitsuku’ through the website of ‘pandorabots’. The conversations were compared, and their
linguistic variables were distinguished according to the following dimensions: words per
message and per conversation, messages per conversation, lexical diversity, frequency of
profanity and use of abbreviations, acronyms and emoticons. During the last few years, both
linguists and AI researchers have been compelled to deal with problems of context, syntax,
semantics and pragmatics (Rosenberg, 1975). There are studies that address the issue of
cooperation between linguistics and natural language processing (NLP) that focus on how
chatbots communicate in writing with humans. However, this study is focused on humans,
evaluating the language and distinguishing the linguistic characteristics used from the side of
people conversing with a chatbot. The results showed that student-chatbot messages contained
fewer words per message than those sent to another student, but students sent more than twice
as many messages to the chatbot than to their peers. The study revealed that there is a higher
level of motivation in students when they engage in conversations with the artificial agent vs
other students.
Degree
Student essay
View/ Open
Date
2020-03-02Author
Silkej, Eirini
Keywords
engelska
English learner
Natural language processing
Artificial Intelligence
AI
Linguistics and AI
Text messaging
Instant Messaging
IM
Chatbot
Mitsuku
Computermediated communication
CMC
Series/Report no.
SPL kandidatuppsatser, engelska
SPL 2019-074
Language
eng