@inproceedings{e11f5bdc71af4ee5ae79446b41f2ff5c,
title = "Oh the places you{\textquoteright}ll share: An affordances-based model of social media posting behaviors",
abstract = "With rising use of multiple social network sites (SNSs), people now have an increasing number of options for audience, media, and other SNS features at their disposal. In this paper, our goal is to build machine learning models that can predict people{\textquoteright}s multi-SNS posting decisions, thus enabling technology that can personalize and augment current SNS use. We explore affordances—the perceived utilities of a SNS{\textquoteright}s features—for creating these models. We build an affordance-based model using data collected from a survey about people{\textquoteright}s multi-SNS posting behavior (n = 674). Our model predicts posting decisions that are ∼35% more accurate compared to a random baseline, and ∼10% more accurate than predictions based on SNS popularity.",
keywords = "Affordances, Social media ecosystem, Usage models",
author = "Harmanpreet Kaur and Isaac Johnson and Miller, {Hannah J.} and Terveen, {Loren G.} and Cliff Lampe and Brent Hecht and Lasecki, {Walter S.}",
note = "Publisher Copyright: Copyright held by the owner/author(s). Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 2018 CHI Conference on Human Factors in Computing Systems, CHI EA 2018 ; Conference date: 21-04-2018 Through 26-04-2018",
year = "2018",
month = apr,
day = "20",
doi = "10.1145/3170427.3188601",
language = "English (US)",
series = "Conference on Human Factors in Computing Systems - Proceedings",
publisher = "Association for Computing Machinery",
booktitle = "CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems",
}