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Understanding Short-term Changes in Online Activity Sessions

Authors:

Karthik Subbian,

Kristina LermanAuthors Info & Claims

WWW '17 Companion: Proceedings of the 26th International Conference on World Wide Web Companion

Pages 555 - 563

https://doi.org/10.1145/3041021.3054203

Published: 03 April 2017 Publication History

Abstract

Online activity is characterized by regularities such as diurnal and weekly patterns, reflecting human circadian rhythms and work and leisure schedules. Using data from the online social networking site Facebook, we uncover temporal patterns at a much smaller time scale: within individual sessions. Longer sessions have different characteristics than shorter ones, and this distinction is already visible in the first minute of a person's session activity. This allows us to predict the ultimate length of his or her session and how much content the person will see. The length of the session and other factors are in turn predictive of when the individual will return. Within a session, the amount of time a person spends on different kinds of content depends on both the person's demographic attributes, such as age and the number of Facebook friends, and the length of the time elapsed since the start of the session. We also find that liking and commenting is very non-uniformly distributed between sessions. Predictions of session duration and activity can potentially be leveraged to more efficiently cache content, especially to mobile devices in places with poor communications infrastructure, in order to improve user online experience.

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Cited By

Gómez-Zará DLiu YNeves LShah NBos M(2024)Unpacking the exploration–exploitation tradeoff on SnapchatComputers in Human Behavior10.1016/j.chb.2023.108014150:COnline publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1016/j.chb.2023.108014
Tan PRen X(2023)Rhythm Research in Interactive System Design: A Literature ReviewInternational Journal of Human–Computer Interaction10.1080/10447318.2023.229462841:1(31-50)Online publication date: 27-Dec-2023
https://doi.org/10.1080/10447318.2023.2294628
Saha KLiu YVincent NChowdhury FNeves LShah NBos MKitamura YQuigley AIsbister KIgarashi TBjørn PDrucker S(2021)AdverTiming Matters: Examining User Ad Consumption for Effective Ad Allocations on Social MediaProceedings of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411764.3445394(1-18)Online publication date: 6-May-2021
https://dl.acm.org/doi/10.1145/3411764.3445394
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Index Terms

Understanding Short-term Changes in Online Activity Sessions
1. Information systems
  1. Information systems applications

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cover image ACM Other conferences

WWW '17 Companion: Proceedings of the 26th International Conference on World Wide Web Companion

April 2017

1738 pages

ISBN:9781450349147

General Chairs:
Rick Barrett
W3Events
,
Rick Cummings
Murdoch University
,
Program Chairs:
Eugene Agichtein
Emory University
,
Evgeniy Gabrilovich
Google Research

Sponsors

IW3C2: International World Wide Web Conference Committee

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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International World Wide Web Conferences Steering Committee

Republic and Canton of Geneva, Switzerland

Publication History

Published: 03 April 2017

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Army Research Office

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WWW '17

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IW3C2

WWW '17: 26th International World Wide Web Conference

April 3 - 7, 2017

Perth, Australia

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WWW '17 Companion Paper Acceptance Rate 164 of 966 submissions, 17%;

Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

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https://dl.acm.org/doi/10.1016/j.chb.2023.108014
Tan PRen X(2023)Rhythm Research in Interactive System Design: A Literature ReviewInternational Journal of Human–Computer Interaction10.1080/10447318.2023.229462841:1(31-50)Online publication date: 27-Dec-2023
https://doi.org/10.1080/10447318.2023.2294628
Saha KLiu YVincent NChowdhury FNeves LShah NBos MKitamura YQuigley AIsbister KIgarashi TBjørn PDrucker S(2021)AdverTiming Matters: Examining User Ad Consumption for Effective Ad Allocations on Social MediaProceedings of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411764.3445394(1-18)Online publication date: 6-May-2021
https://dl.acm.org/doi/10.1145/3411764.3445394
Zeng YSapienza AFerrara E(2021)The Influence of Social Ties on Performance in Team-Based Online GamesIEEE Transactions on Games10.1109/TG.2019.292322313:4(358-367)Online publication date: Dec-2021
https://doi.org/10.1109/TG.2019.2923223
Diwan AKumar Swain RMinz SParganiha APati A(2020)Ultradian, circadian, and circaseptan rhythms in the patterns of usage of Facebook messengerBiological Rhythm Research10.1080/09291016.2020.174774153:2(341-349)Online publication date: 1-Apr-2020
https://doi.org/10.1080/09291016.2020.1747741
Matsui ASapienza AFerrara E(2019)Does Streaming Esports Affect Players’ Behavior and Performance?Games and Culture10.1177/155541201983809515:1(9-31)Online publication date: 14-Apr-2019
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Alipourfard NFennell PLerman KChang YZhai CLiu YMaarek Y(2018)Can you Trust the Trend?Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining10.1145/3159652.3159684(19-27)Online publication date: 2-Feb-2018
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Lerman K(2017)Computational social scientist beware: Simpson’s paradox in behavioral dataJournal of Computational Social Science10.1007/s42001-017-0007-41:1(49-58)Online publication date: 20-Nov-2017
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