The Effect of Twitter App Policy Changes on the Sharing of Spatial Information through Twitter Users

Q3 Social Sciences
Jiping Cao, H. Hochmair, Fisal Basheeh
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引用次数: 4

Abstract

Social media data have been widely used to gain insight into human mobility and activity patterns. Despite their abundance, social media data come with various data biases, such as user selection bias. In addition, a change in the Twitter app functionality may further affect the type of information shared through tweets and hence influence conclusions drawn from the analysis of such data. This study analyzes the effect of three Twitter app policy changes in 2015, 2017, and 2019 on the tweeting behavior of users, using part of London as the study area. The policy changes reviewed relate to a function allowing to attach exact coordinates to tweets by default (2015), the maximum allowable length of tweet posts (2017), and the limitation of sharing exact coordinates to the Twitter photo app (2019). The change in spatial aspects of users’ tweeting behavior caused by changes in user policy and Twitter app functionality, respectively, is quantified through measurement and comparison of six aspects of tweeting behavior between one month before and one month after the respective policy changes, which are: proportion of tweets with exact coordinates, tweet length, the number of placename mentions in tweet text and hashtags per tweet, the proportion of tweets with images among tweets with exact coordinates, and radius of gyration of tweeting locations. The results show, among others, that policy changes in 2015 and 2019 led users to post a smaller proportion of tweets with exact coordinates and that doubling the limit of allowable characters as part of the 2017 policy change increased the number of place names mentioned in tweets. The findings suggest that policy changes lead to a change in user contribution behavior and, in consequence, in the spatial information that can be extracted from tweets. The systematic change in user contribution behavior associated with policy changes should be specifically taken into consideration if jointly analyzing tweets from periods before and after such a policy change.
推特应用政策变化对推特用户空间信息共享的影响
社交媒体数据已被广泛用于深入了解人类的流动性和活动模式。尽管社交媒体数据非常丰富,但也存在各种数据偏差,比如用户选择偏差。此外,Twitter应用功能的变化可能会进一步影响通过推文共享的信息类型,从而影响对这些数据的分析得出的结论。本研究以伦敦部分地区为研究区域,分析了2015年、2017年和2019年三次推特应用程序政策变化对用户推文行为的影响。审查的政策变化涉及允许默认将精确坐标附加到推文的功能(2015年),推文的最大允许长度(2017年),以及限制将精确坐标共享到推特照片应用程序(2019年)。通过对用户政策变化和推特应用功能变化前后一个月的6个方面的推文行为进行测量和比较,量化用户政策变化和推特应用功能变化对用户推文行为空间方面的影响,分别为:精确坐标推文的比例、推文长度、每条推文中提及地名的数量和标签数、精确坐标推文中包含图片的推文比例、推文位置的旋转半径。结果显示,除其他外,2015年和2019年的政策变化导致用户发布精确坐标的推文比例减少,2017年政策变化将允许的字符限制增加了一倍,增加了推文中提到的地名数量。研究结果表明,政策变化导致用户贡献行为的变化,从而导致可以从推文中提取的空间信息的变化。在联合分析政策变化前后的推文时,需要特别考虑到政策变化带来的用户贡献行为的系统性变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Human Geographies
Human Geographies Social Sciences-Geography, Planning and Development
CiteScore
1.10
自引率
0.00%
发文量
7
审稿时长
8 weeks
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