Alastair J. Gill

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Dewaele and Furnham predict that in oral language Extraverts prefer to produce what they term implicit language. They use: more pronouns, adverbs and verbs; and fewer nouns, adjectives and prepositions. However, communication in a computermediated environment, such as e-mail, might disrupt these preferences. Also, other personality dimensions, such as(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)
We investigate the impact of computer-mediated interaction on person perception. In particular, we study how traits important for socialisation and collaboration—Extraversion and Neuroticism—can be detected from the text of an e-mail communication. We have previously shown how Extraversion influences people’s language production in electronic communication,(More)
Personality is a fundamental component of an individual’s affective behavior. Previous work on personality classification has emerged from disparate sources: Varieties of algorithms and feature-selection across spoken and written data have made comparison difficult. Here, we use a large corpus of blogs to compare classification feature selection; we also(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)
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)
To what extent does the wording and syntactic form of people’s writing reflect their personalities? Using a bottom-up stratified corpus comparison, rather than the top-down content analysis techniques that have been used before, we examine a corpus of e-mail messages elicited from individuals of known personality, as measured by the Eysenck Personality(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)