Theories, Methods and Current Research on Emotions in Library and Information Science, Information Retrieval and Human-Computer Interaction

✨ Summary

Paper summary

This review examines how emotions are defined, theorized, measured, and applied in Library and Information Science, Information Retrieval, and Human-Computer Interaction. It emphasizes that emotions influence cognition, perception, decision-making, motivation, satisfaction, and interaction with information systems.

The paper compares two broad families of emotion theories. Cognitive and appraisal theories explain emotions through evaluations of events and their relevance to an individual’s well-being. Somatic theories emphasize bodily responses and evolved mechanisms of emotional expression. It also contrasts discrete models, which represent emotions as basic categories such as happiness, fear, anger, sadness, disgust, and surprise, with dimensional models, which represent affect using dimensions such as valence and arousal.

Three major measurement approaches are reviewed:

• Neuro-physiological methods, including pulse, blood pressure, skin conductance, respiration, facial-muscle activity, and EEG. These can detect short-term bodily changes but are often intrusive, costly, noisy, and difficult to map to specific emotions.
• Observer methods, including facial-expression, speech, gesture, and interaction-log analysis. These can be relatively unobtrusive and support automated recognition, but they are highly dependent on context and environmental conditions and may detect expressions rather than underlying emotions.
• Self-report methods, including diaries, interviews, questionnaires, think-aloud protocols, and standardized scales such as PANAS and STAI. These provide direct access to subjective experience but depend on participants’ awareness, memory, language, and willingness to report emotions.

Across information-search studies, positive emotions are commonly associated with successful task completion, ease of use, interest, effective navigation, and satisfactory results. Negative emotions are associated with uncertainty, system failures, difficult tasks, inadequate system knowledge, and difficulty finding answers. Affect is also linked to search strategies, persistence, motivation, satisfaction, self-efficacy, system acceptance, and search performance. The review recommends combining multiple measurement methods because no single method provides a complete account of an emotional episode.

The authors conclude that emotion research in HCI, LIS, and IR was still methodologically immature at the time of publication. They identify inconsistent definitions of emotion-related concepts, limited comparability across studies, insufficient interdisciplinary cross-referencing, and the difficulty of interpreting physiological or expressive signals without contextual information as central challenges.

Evidence of influence

Later information-behavior research explicitly characterizes this article as an overview of affective factors in information retrieval, information searching, and HCI, using it as a foundation for more focused analyses of affect in Kuhlthau’s information-search-process model. (informationr.net) A subsequent study by Lopatovska developed a model relating primary emotions, secondary emotions, mood, search actions, performance, and outcome quality, extending themes identified in the review. (asistdl.onlinelibrary.wiley.com)

The review has also been cited in later work on information-seeking self-efficacy, emotion expression in online information sharing, affective tagging of art images, and physiological-signal-based information retrieval research. These citations indicate continuing use of the paper as a conceptual and methodological reference rather than evidence of a single commercial system directly derived from it. (sciencedirect.com)