Alastair J. Gill

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Emotion is central to human interactions, and automatic detection could enhance our experience with technologies. We investigate the linguistic expression of fine-grained emotion in 50 and 200 word samples of real blog texts previously coded by expert and naive raters. Content analysis (LIWC) reveals angry authors use more affective language and negative(More)
Personal weblogs (blogs), provide individuals with the opportunity to write freely and express themselves online in the presence of others. In such situations, what do bloggers write about, and what are their motivations for blogging? Using a large blog corpus annotated with the LIWC text analysis program, we examine the content of blogs to provide insight(More)
This study examines the relationship between linguistic mimicry and trust establishment in a text-chat environment. Twenty-six participant pairs engaged in a social dilemma investment game and chatted via Instant Messenger (IM) after every five rounds of investment. Results revealed that, <i>within chat sessions</i>, lexical mimicry (repetition of words or(More)
This paper examines how different forms of linguistic similarity in a text-chat environment relate to the establishment of interpersonal trust. Sixty-two pairs played an iterative social dilemma investment game and periodically communicated via Instant Messenger (IM). Novel automated and manual analysis techniques identify linguistic similarity at content,(More)
Being able to automatically perceive a variety of emotions from text alone has potentially important applications in CMC and HCI that range from identifying mood from online posts to enabling dynamically adaptive interfaces. However, such ability has not been proven in human raters or computational systems. Here we examine the ability of naive raters of(More)
Automatic classification of personality from language depends upon large quantities of relevant training data, which raises two potential problems. First, collecting personality information from the author or speaker can be invasive and expensive, especially in sensitive contexts. Second, issues of context or genre can reduce the usefulness of available(More)
Variation in language style can lead to different perceptions of the interaction, and different behaviour outcomes. Using the CRAG 2 language generation system we examine how accurately judges can perceive character personality from short, automatically generated dialogues, and how alignment (similarity between speakers) alters judge perceptions of the(More)