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Sequential Analysis of Player Behavior

Published: 05 October 2015 Publication History

Abstract

Understanding how interaction unfolds over time is a key factor for understanding the dynamics aspects of player behavior. Thus far, analysis of sequential patterns of player behavior has, however, mainly focused on discovering frequently recurring patterns. However, frequency of occurrence is not always a reliable indicator of a pattern's importance as infrequent patterns can also offer valuable insights about in-game behavior. In this paper we thus propose the use of lag sequential analysis (LSA) -- which, rather than relying on frequency counts, makes use of statistical methods to determine the significance of sequential transitions -- to aid analysis of behavioral streams of players. For this purpose we apply LSA to in-game data of two well-known games. The meaningfulness of the identified sequences is verified by comparing them to documented and established strategies. In addition, results obtained through LSA are discussed in relation to results from frequency-based sequence mining. Our results suggest that LSA is a promising complement to frequency based methods for analyzing sequential behavior patterns of players.

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  • (2021)“Try, Try, Try Again:” Sequence Analysis of User Interaction Data with a Voice User InterfaceProceedings of the 3rd Conference on Conversational User Interfaces10.1145/3469595.3469613(1-8)Online publication date: 27-Jul-2021
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cover image ACM Conferences
CHI PLAY '15: Proceedings of the 2015 Annual Symposium on Computer-Human Interaction in Play
October 2015
852 pages
ISBN:9781450334662
DOI:10.1145/2793107
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 the author(s) 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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Publication History

Published: 05 October 2015

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Author Tags

  1. frequent sequence mining
  2. game analytics
  3. lag sequential analysis
  4. player behavior
  5. transition probabilities

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CHI PLAY '15 Paper Acceptance Rate 40 of 144 submissions, 28%;
Overall Acceptance Rate 421 of 1,386 submissions, 30%

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The Annual Symposium on Computer-Human Interaction in Play
October 14 - 17, 2024
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Cited By

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  • (2022)Building a Behavioral Profile and Assessing the Skill of Video Game PlayersIEEE Sensors Journal10.1109/JSEN.2021.312708322:1(481-488)Online publication date: 1-Jan-2022
  • (2021)“Try, Try, Try Again:” Sequence Analysis of User Interaction Data with a Voice User InterfaceProceedings of the 3rd Conference on Conversational User Interfaces10.1145/3469595.3469613(1-8)Online publication date: 27-Jul-2021
  • (2021)Immersion experiences and behavioural patterns in game‐based learningBritish Journal of Educational Technology10.1111/bjet.1309352:5(1981-1999)Online publication date: 25-Apr-2021
  • (2021)An Empirical Study of Trends of Popular Virtual Reality Games and Their ComplaintsIEEE Transactions on Games10.1109/TG.2021.305728813:3(275-286)Online publication date: Sep-2021
  • (2021)Player Behavior Modeling for Enhancing Role-Playing Game EngagementIEEE Transactions on Computational Social Systems10.1109/TCSS.2021.30522618:2(464-474)Online publication date: Apr-2021
  • (2021)Comprehensive review and classification of game analyticsService Oriented Computing and Applications10.1007/s11761-020-00303-z15:2(141-156)Online publication date: 1-Jun-2021
  • (2020)Statistical Significance Testing at CHI PLAY: Challenges and Opportunities for More TransparencyProceedings of the Annual Symposium on Computer-Human Interaction in Play10.1145/3410404.3414229(4-18)Online publication date: 2-Nov-2020
  • (2020)Reading Between the Lines – Towards an Algorithm Exploiting In-game Behaviors to Learn Preferences in Gameful SystemsProceedings of the 15th International Conference on the Foundations of Digital Games10.1145/3402942.3403016(1-12)Online publication date: 15-Sep-2020
  • (2020)Bombalytics: Visualization of Competition and Collaboration Strategies of Players in a Bomb Laying GameComputer Graphics Forum10.1111/cgf.1396539:3(89-100)Online publication date: 18-Jul-2020
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