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RSWK

Informationsgesellschaft / Sozialer Wandel / Massendaten / Datenanalyse / Informationsüberlastung / Datenschutz / Aufsatzsammlung
World Wide Web / Privatsphäre / Datenschutz / Aufsatzsammlung (BVB)

Subject

Informationsgesellschaft / Sozialer Wandel / Massendaten / Datenanalyse / Informationsüberlastung / Datenschutz / Aufsatzsammlung
World Wide Web / Privatsphäre / Datenschutz / Aufsatzsammlung (BVB)

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RSWK

Natürlichsprachiges System / Information Extraction / Automatische Inhaltsanalyse / Zusammenfassung / Aufsatzsammlung

Subject

Natürlichsprachiges System / Information Extraction / Automatische Inhaltsanalyse / Zusammenfassung / Aufsatzsammlung

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RSWK

Text Mining / Aufsatzsammlung

Subject

Text Mining / Aufsatzsammlung

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Content

Bergman and Whittaker report that many of us use hierarchical folders for our personal digital organizing. Critics of this method point out that information is hidden from sight in folders that are often within other folders so that we have to remember the exact location of information to access it. Because of this, information scientists suggest other methods: search, more flexible than navigating folders; tags, which allow multiple categorizations; and group information management. Yet Bergman and Whittaker have found in their pioneering PIM research that these other methods that work best for public information management don't work as well for personal information management. Bergman and Whittaker describe personal information collection as curation: we preserve and organize this data to ensure our future access to it. Unlike other information management fields, in PIM the same user organizes and retrieves the information. After explaining the cognitive and psychological reasons that so many prefer folders, Bergman and Whittaker propose the user-subjective approach to PIM, which does not replace folder hierarchies but exploits these unique characteristics of PIM.

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Abstract

An important part of our information-gathering behavior has always been to find out what other people think. With the growing availability and popularity of opinion-rich resources such as online review sites and personal blogs, new opportunities and challenges arise as people can, and do, actively use information technologies to seek out and understand the opinions of others. The sudden eruption of activity in the area of opinion mining and sentiment analysis, which deals with the computational treatment of opinion, sentiment, and subjectivity in text, has thus occurred at least in part as a direct response to the surge of interest in new systems that deal directly with opinions as a first-class object. Opinion Mining and Sentiment Analysis covers techniques and approaches that promise to directly enable opinion-oriented information-seeking systems. The focus is on methods that seek to address the new challenges raised by sentiment-aware applications, as compared to those that are already present in more traditional fact-based analysis. The survey includes an enumeration of the various applications, a look at general challenges and discusses categorization, extraction and summarization. Finally, it moves beyond just the technical issues, devoting significant attention to the broader implications that the development of opinion-oriented information-access services have: questions of privacy, vulnerability to manipulation, and whether or not reviews can have measurable economic impact. To facilitate future work, a discussion of available resources, benchmark datasets, and evaluation campaigns is also provided. Opinion Mining and Sentiment Analysis is the first such comprehensive survey of this vibrant and important research area and will be of interest to anyone with an interest in opinion-oriented information-seeking systems.