A Mobile Tool for Collecting and Labeling Data on Twitter's Network Sociability Practices

Guilherme Augusto da Silva Ferreira, Alan Keller Gomes
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引用次数: 1

Abstract

This work presents a mobile tool for collecting and labeling data about Twitter's sociability practices. Such data are related to the execution of functionalities such as Tweet, Comment, Retweet and Like. During the capture, the data are labeled with a sequence of actions, which is learned via the GSP algorithm, and the polarity of sentiment contained in the tweet. At the end, the data are processed to compute the volume of Bourdieusian Social Capital (BSC) of the profile and are also available for the user of the tool to export them. In addition, the composition of the BSC from the polarity of sentiment is computed.
收集和标记Twitter网络社交实践数据的移动工具
这项工作提出了一个移动工具,用于收集和标记有关Twitter社交实践的数据。这些数据与Tweet、Comment、Retweet和Like等功能的执行有关。在捕获过程中,数据被标记为一系列动作,这是通过GSP算法学习的,以及tweet中包含的情绪极性。最后,对数据进行处理以计算配置文件的布尔迪厄社会资本(BSC)的量,并且也可供工具的用户导出它们。此外,根据情感极性计算平衡记分卡的组成。
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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