Jasy Suet Yan Liew

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Qualitative content analysis is commonly used by social scientists to understand the practices of the groups they study, but it is often infeasible to manually code a large text corpus within a reasonable time frame and budget. To address this problem, we are building a software tool to assist social scientists performing content analysis. We present our(More)
This paper describes EmoTweet-28, a carefully curated corpus of 15,553 tweets annotated with 28 emotion categories for the purpose of training and evaluating machine learning models for emotion classification. EmoTweet-28 is, to date, the largest tweet corpus annotated with fine-grained emotion categories. The corpus contains annotations for four facets of(More)
We propose a semi-automatic approach for content analysis that leverages machine learning (ML) being initially trained on a small set of hand-coded data to perform a first pass in coding, and then have human annotators correct machine annotations in order to produce more examples to retrain the existing model incrementally for better performance. In this(More)
This paper explores the formative user interface design of a socially-interactive dressing room. The socially-interactive dressing room allows shoppers to talk to their friends in real time for opinions on their garment purchasing decisions. Our work is motivated by the observation that shoppers who lack fashion sense often rely on their friends' opinions(More)
Determining the influence of organizational Twitter accounts is far from an exact science, although numerous companies (most prominently Klout) have recently sought to find appropriate metrics and algorithms. Klout, a company that measures influence on the social web, recently ranked Syracuse University (SU) as the No. 2 "Most Influential College on(More)
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