为了确定推特上信息传播的最重要因素,使用广谱和重量

Aisyah Rafi' Addani, Turmudi Turmudi, Imam Sujarwo
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引用次数: 0

摘要

图是一个非空集合,其成员是顶点和边,其中边连接了这些顶点的几对;同样,社交媒体通过兴趣、关系、好恶将用户彼此联系起来。全球化时代科技的飞速发展使得社交媒体成为了更有效的信息来源,其中之一就是Twitter,全世界有2.8亿人在使用它。这项研究涉及100名Twitter用户,他们被归类为印度尼西亚的影响者,拥有超过1万名粉丝,通过有向加权图可视化他们与其他用户的关系。首先,使用Python软件中的Twecoll脚本对数据进行过滤,然后使用Gephi软件以有向加权图的形式对数据进行可视化。计算中心性值以确定在网络上传播信息的有影响力的影响者。根据研究结果,通过中心性计算的结果发现,以下@dearmyths账户列表中收集的100位网红的网络模式,有96个点,1883个边,权重最高的边是@detikcom,其次是@ivanlanin和@ernestprakasa作为可以在网络上传播信息的账户。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Penerapan Graf Berarah dan Berbobot untuk Mengetahui Inluencer yang Paling Berpengaruh dalam Penyebaran Informasi pada Twitter
A graph is a non-empty set whose members are vertices and edges, where the edges connect several pairs of these vertices; likewise, social media connects users with each other through interests, relationships, likes and dislikes. The rapid development of technology in the era of globalization has made social media a more effective source of information, one of them is Twitter which has been used by 280 million people in the world. This research involves 100 Twitter users who are classified as Influencers in Indonesia who have more than 10,000 followers by visualizing their relationship with other users followed by them with a directed and weighted graph. First, the data is filtered using the Twecoll script in Python software, then the data is visualized using the Gephi software in the form of a directed and weighted graph. The centrality value is calculated to determine the influential influencers in spreading information on the network. Based on the results of the study, it was found that the network pattern of 100 Influencers that had been collected in the following list of @dearmyths accounts, there were 96 points and 1883 sides with the side having the highest weight being @detikcom, followed by @ivanlanin and @ernestprakasa through the results of centrality calculations as accounts that can disseminate information on the network.
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