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Abstract

This empirical study offers a new theoretical perspective in information behavior research by identifying interrelationships between certain information behaviors. While previous work recognizes the iterative nature of information acquisition, information behavior research has so far been dominated by the identification and conceptual elaboration of discrete behaviors. We introduce the theoretical concept of "information behavior patterns" to characterize the intricate connectedness of information interaction in an arts and crafts context. A qualitative study comprising naturalistic observation and semi-structured interviews with 20 arts and crafts hobbyists was conducted in two "browse-first" information environments that support various forms of active and passive information acquisition: Pinterest and a brick-and-mortar crafts store. Findings revealed a variety of information behavior patterns across both environments. We illustrate several of these through in-depth discussions of two specific information acquisition sessions. We visualize observed patterns from these sessions to illustrate the interweaving of active, passive acquisition, and personal goals. Our findings demonstrate the complex interconnectedness of human information behavior, highlighting the importance of going beyond compartmentalizing behaviors into "buckets" when trying to understand the complex, dynamic, and evolving nature of information interaction.

Series

JASIS&Tspecial issue on information behavior and information practices theory

Source

Journal of the Association for Information Science and Technology. 73(2022) no.4, S.594-608

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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.

LCSH

Information behavior
Information retrieval

Series

Foundations and trends(r) in information retrieval; 2,1/2

Subject

Information behavior
Information retrieval