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Going back in Time: An Investigation of Social Media Re-finding

Published: 07 July 2016 Publication History

Abstract

Social Media (SM) has become a valuable information source to many in diverse situations. In IR, research has focused on real-time aspects and as such little is known about how long SM content is of value to users, if and how often it is re-accessed, the strategies people employ to re-access and if difficulties are experienced while doing so. We present results from a 5 month-long naturalistic, log-based study of user interaction with Twitter, which suggest re-finding to be a regular activity and that Tweets can offer utility for longer than one might think. We shed light on re-finding strategies revealing that remembered people are used as a stepping stone to Tweets rather than searching for content directly. Bookmarking strategies reported in the literature are used infrequently as a means to re-access. Finally, we show that by using statistical modelling it is possible to predict if a Tweet has future utility and is likely to be re-found. Our findings have implications for the design of social media search systems and interfaces, in particular for Twitter, to better support users re-find previously seen content.

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  • (2024)An exploratory study of information re-finding behaviour modes of Chinese college students on social media: video diary analysis from Chinese platformsBehaviour & Information Technology10.1080/0144929X.2024.233126144:3(596-610)Online publication date: 21-Mar-2024
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    SIGIR '16: Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval
    July 2016
    1296 pages
    ISBN:9781450340694
    DOI:10.1145/2911451
    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: 07 July 2016

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    Author Tags

    1. clickstream analysis
    2. re-finding
    3. twitter

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    SIGIR '16 Paper Acceptance Rate 62 of 341 submissions, 18%;
    Overall Acceptance Rate 792 of 3,983 submissions, 20%

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    View all
    • (2024)An exploratory study of information re-finding behaviour modes of Chinese college students on social media: video diary analysis from Chinese platformsBehaviour & Information Technology10.1080/0144929X.2024.233126144:3(596-610)Online publication date: 21-Mar-2024
    • (2023)Managing Personal InformationAdvances in Visual Informatics10.1007/978-981-99-7339-2_1(3-11)Online publication date: 15-Nov-2023
    • (2022)Reflection on future directions: a systematic review of reported limitations and solutions in interactive information retrieval user studiesAslib Journal of Information Management10.1108/AJIM-05-2022-025376:1(104-131)Online publication date: 19-Dec-2022
    • (2021)Towards Understanding Complex Known-Item Requests on RedditProceedings of the 32nd ACM Conference on Hypertext and Social Media10.1145/3465336.3475096(143-154)Online publication date: 30-Aug-2021
    • (2019)Hierarchical Multi-Clue Modelling for POI Popularity Prediction with Heterogeneous Tourist InformationIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2018.284219031:4(757-768)Online publication date: 1-Apr-2019
    • (2018)Other Times Itźs Just Strolling Back Through My TimelineProceedings of the 2018 Conference on Human Information Interaction & Retrieval10.1145/3176349.3176392(130-139)Online publication date: 1-Mar-2018
    • (2017)What's Happening and What HappenedProceedings of the 2017 ACM on Web Science Conference10.1145/3091478.3091484(191-200)Online publication date: 25-Jun-2017
    • (2017)Manipulating the Perception of Credibility in Refugee Related Social Media PostsProceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval10.1145/3020165.3022137(297-300)Online publication date: 7-Mar-2017

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