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Tag expression: tagging with feeling

Published: 03 October 2010 Publication History

Abstract

In this paper we introduce tag expression, a novel form of preference elicitation that combines elements from tagging and rating systems. Tag expression enables users to apply affect to tags to indicate whether the tag describes a reason they like, dislike, or are neutral about a particular item. We present a user interface for applying affect to tags, as well as a technique for visualizing the overall community's affect. By analyzing 27,773 tag expressions from 553 users entered in a 3-month period, we empirically evaluate our design choices. We also present results of a survey of 97 users that explores users' motivations in tagging and measures user satisfaction with tag expression.

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  • (2024)Less Typing, More Tagging: Investigating Tag-based Interfaces in Online Accommodation Review Creation and PerceptionProceedings of the 13th Nordic Conference on Human-Computer Interaction10.1145/3679318.3685369(1-13)Online publication date: 13-Oct-2024
  • (2021)On Interpretation and Measurement of Soft Attributes for RecommendationProceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3404835.3462893(890-899)Online publication date: 11-Jul-2021
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cover image ACM Conferences
UIST '10: Proceedings of the 23nd annual ACM symposium on User interface software and technology
October 2010
476 pages
ISBN:9781450302715
DOI:10.1145/1866029
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 03 October 2010

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Author Tags

  1. community
  2. ratings
  3. tagging
  4. user preference

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Overall Acceptance Rate 561 of 2,567 submissions, 22%

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Cited By

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  • (2024)Less Typing, More Tagging: Investigating Tag-based Interfaces in Online Accommodation Review Creation and PerceptionProceedings of the 13th Nordic Conference on Human-Computer Interaction10.1145/3679318.3685369(1-13)Online publication date: 13-Oct-2024
  • (2021)On Interpretation and Measurement of Soft Attributes for RecommendationProceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3404835.3462893(890-899)Online publication date: 11-Jul-2021
  • (2019)Customized Alumni Portal implementing Natural Language Processing Techniques2019 International Conference on Intelligent Computing and Control Systems (ICCS)10.1109/ICCS45141.2019.9065320(927-931)Online publication date: May-2019
  • (2018)Recommender Systems, Semantic-BasedEncyclopedia of Social Network Analysis and Mining10.1007/978-1-4939-7131-2_116(2137-2147)Online publication date: 12-Jun-2018
  • (2017)Research on an Agent-Based Intelligent Social Tagging Recommendation System2017 9th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)10.1109/IHMSC.2017.17(43-46)Online publication date: Aug-2017
  • (2017)Recommender Systems, Semantic-BasedEncyclopedia of Social Network Analysis and Mining10.1007/978-1-4614-7163-9_116-1(1-11)Online publication date: 4-Aug-2017
  • (2016)Recent developments in affective recommender systemsPhysica A: Statistical Mechanics and its Applications10.1016/j.physa.2016.05.046461(182-190)Online publication date: Nov-2016
  • (2015)The MovieLens DatasetsACM Transactions on Interactive Intelligent Systems10.1145/28278725:4(1-19)Online publication date: 22-Dec-2015
  • (2014)Supporting customers' decision making with Rated TagsProceedings of the Sixteenth International Conference on Electronic Commerce10.1145/2617848.2617849(33-40)Online publication date: 5-Aug-2014
  • (2014)Leveraging the contributory potential of user feedbackProceedings of the 17th ACM conference on Computer supported cooperative work & social computing10.1145/2531602.2531686(956-966)Online publication date: 15-Feb-2014
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