The aim of this paper is to investigate the feasibility of predicting the gender of a text document’s author using linguistic evidence. For this purpose, termand style-based classification techniques are evaluated over a large collection of chat messages. Prediction accuracies up to 84.2% are achieved, illustrating the applicability of these techniques to gender prediction. Moreover, the revers...

Instant Messaging (IM) chat sessions are real-time, text-based conversations which can be analyzed using dialogue-act models. Dialogue acts represent the semantic information of an utterance, however, messages must be segmented into utterances before classification can take place. We describe and compare two statistical methods for automatic utterance segmentation and dialogue-act classificatio...

In this paper we present a 3D animated agent with synthesized face, speech and behavior, which is capable of automatic motion generation with a little user support of text annotation. Users without artistic skills are also capable of easy creation and extension of their own agents with tailor-made appearance and motion. Its implementation and compact size allows for easy use on the Internet as ...

This paper describes a new experimental system, the Automated Deception Analysis Machine (ADAM), that was used to conduct automated, chat-based interviews and perform deception detection of the text-based responses. 108 participants were interviewed by this new chatbot agent and they provided 3,162 chat-based responses. Several new metrics were discovered that highly correlate to deceit. ADAM c...

Machine Translation system accuracies are often brought down due to inaccurate Language Detection (LD) of input phrases. The Language detection accuracy is further affected when the inputs are short and contain ungrammatical phrases, especially in a multilingual mobile game setting. Chat messages in mobile games are often short as they are typed on mobile devices and contain slang as a common c...

W hen two people chat face to face, they know the conversation's context—each knows, for example , the other person's location, what he or she is doing, who else is nearby, and the room's condition (lighting, sound, and so forth). There is also significant communication through facial and other nonverbal cues. Knowing such information makes the conversation richer. However, when you chat with s...

We report findings from a chat log analysis of a support group in which 2–5 patients and one or two facilitators chatted in a virtual space; weekly sessions lasted 1.5 hrs. each, and we followed them over five years. In the virtual space, participants were represented by avatars with emotional expressions. Chat messages were analysed with a text-mining tool, exploring whether positive emotion w...

The ephemeral nature of human communication via networks today poses interesting and challenging problems for information technologists. The sheer volume of communication in venues such as email, newsgroups, and chat precludes manual techniques of information management. Currently, no systematic mechanisms exist for accumulating these artifacts of communication in a form that lends itself to th...