Population estimation using Twitter for a specific space
Population estimation using Twitter for a specific space
复制标题
使用 Twitter 对特定空间进行人口估算
DOI：
10.1108/dta-03-2020-0065
复制
发表时间：
2021
影响因子：
1.6
通讯作者：
Tsuda Kazuhiko
中科院分区：
文献类型：
--
作者：
Hara Hiroki;Fujita Yoshikatsu;Tsuda Kazuhiko
目的本文旨在利用 Twitter 的实时财产和位置信息数据，根据发布的推文数量及其发送者来估计特定空间中的人口。设计/方法/方法将要估计的人口设置为日本职业棒球太平洋联盟的六支棒球队在各队主体育场举行的每场比赛的上座率。分析了出席率和 Twitter 数据之间的关系，并使用 Twitter 数据的回归模型来估计出席率。发现出席率和推文用户的相关系数往往大于出席率和推文数量的相关系数。此外，结合Twitter数据、游戏数据和天气数据估计出席率的几种回归模型的比较和评估显示了Twitter数据的有用性，并且使用推文用户数量提高了人口估计的准确性。 原创性/价值虽然有很多关于使用Twitter数据进行事件检测或位置识别的研究，但还没有关于利用Twitter数据的“时间信息”和“位置信息”特征来估计特定空间中的人口的研究报道。使用包含用户消息的 Twitter 数据来估计人口可以扩展到各种类型的分析，例如对该空间中群体的感受和意见的分析。
PurposeThis paper aims to estimate the population in a specific space from the numbers of posted tweets and their senders, using Twitter's real-time property and location information data.Design/methodology/approachThe population to be estimated was set to be the attendance at each game among the six baseball teams of the Japan Professional Baseball Pacific League held at the main stadium of each team. The relation between the attendance and Twitter data was analyzed, and regression models using Twitter data were used to estimate the attendances.FindingsThe correlation coefficient tended to be larger for the attendance and tweeting users than for the attendance and that of the number of tweets. Furthermore, the comparison and evaluation of several regression models combining Twitter data, game data and weather data for estimating the attendance showed the usefulness of Twitter data, and that using the number of tweeting users improved the accuracy of population estimation.Originality/valueWhile there are many studies on event detection or location identification using Twitter data, no study has been reported on the estimation of the population in a specific space using “time information” and “location information” characteristic of Twitter data. Using Twitter data, which contains users' messages, for estimating the population can be extended to various types of analyses, such as the analysis of feelings and opinions of the groups in the space.