Open AccessTwitter and Online Prostitution: The Communication Network of Online Prostitution in Twitter
Author(s) -
Siska Armawati Sufa,
Andry Alamsyah,
Suwandi Sumartias,
Feliza Zubair,
Susie Perbawasari
Publication year - 2022
Publication title -
webology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.259
H-Index - 18
ISSN - 1735-188X
DOI - 10.14704/web/v19i1/web19186
Subject(s) - set (abstract data type) , computer science , plug in , social network (sociolinguistics) , process (computing) , social network analysis , world wide web , data science , social media , internet privacy , programming language , operating system
The information developments and communication technology also has a negative side. This study is aimed to determine the online prostitution communication network on Twitter and understanding of online prostitution on Twitter. This study uses SNA (Social Network Analysis). SNA views social relations as a theory of networks consisting of nodes and relationships (also called edges, links, or connections). Nodes are individual actors in the network and the relationships are between actors. The data set used in this study is tweet data from Twitter, with the keyword samples being “openBO”. The hashtags were chosen because they are the most widely used the hashtags for online prostitution. The data is taken with a period between January 2020 to December 2020. The data is taken and processed using NodeXL Basic, one of the plugins for Microsoft Excel that can be used to process data from social networks. This research found there are 3,673 nodes and 54,969 edges. The hashtags utilization is usually utilized by online whores to advance their administrations. A few prostitutes are independent, it is implying that they don’t connect with others in advancing business sex administrations. It is not reliant upon pimps since pimps mean to lessen their business chain.