Understand and assess people’s procrastination by mining computer usage log

Ming He, Yan Chen, Qi Liu, Yong Ge, Enhong Chen, Guiquan Liu, Lichao Liu, Xin Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Although the computer and Internet largely improve the convenience of life, they also result in various problems to our work, such as procrastination. Especially, today’s easy access to Internet makes procrastination more pervasive for many people. However, how to accurately assess user procrastination is a challenging problem. Traditional approaches are mainly based on questionnaires, where a list of questions are often created by experts and presented to users to answer. But these approaches are often inaccurate, costly and time-consuming, and thus can not work well for a large number of ordinary people. In this paper, to the best of our knowledge, we are the first to propose to understand and assess people’s procrastination by mining user’s behavioral log on computer. Specifically, as the user’s behavior log is time-series, we first propose a simple procrastination identification model based on the Markov Chain to assess user procrastination. While the simple model can not directly depict reasons of user procrastination, we extract some features from computer logs, which successfully bridge the gap between user behaviors on computer and psychological theories. Based on the extracted features, we design a more sophisticated model, which can accurately identify user procrastination and reveal factors that may cause user’s procrastination. The revealed factors could be used to further develop programs to mitigate user’s procrastination. To validate the effectiveness of our model, we conduct experiments on a real-world dataset and procrastination questionnaires with 115 volunteers. The results are consistent with psychological findings and validate the effectiveness of the proposed model. We believe this work could provide valuable insights for researchers to further exploring procrastination.

Original languageEnglish (US)
Title of host publicationKnowledge Science, Engineering and Management - 11th International Conference, KSEM 2018, Proceedings
EditorsWeiru Liu, Bo Yang, Fausto Giunchiglia
Number of pages13
ISBN (Print)9783319993645
StatePublished - 2018
Externally publishedYes
Event11th International Conference on Knowledge Science, Engineering and Management, KSEM 2018 - Changchun, China
Duration: Aug 17 2018Aug 19 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11061 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference11th International Conference on Knowledge Science, Engineering and Management, KSEM 2018

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


Dive into the research topics of 'Understand and assess people’s procrastination by mining computer usage log'. Together they form a unique fingerprint.

Cite this