TWITTER FOLLOWERS ANALYSIS SENTIMENT WITH SUPPORT VECTOR MACHINE METHOD

TEGUH RAMADHANY

Informasi Dasar

75 kali
18.04.286
302.302 85
Karya Ilmiah - Skripsi (S1) - Reference

The user of microblogging services, such as Twitter, use the count of followers as a measure of its reputation or influence. Twitter is a promotional tool used by an increasing number of tech-oriented business. It is a social networking and micro-blogging service whose user send and receive 140-characters called tweets between their followers. Twitter user are hoping to boost their status by buying phony followers, which have spawned a multimillion-dollar business with some people attempting to cash in by abusing the social network. While other rely on pyramid scheme to turn non-paying customers into followers. With Support Vector Machine (SVM) method, we will analyze and implement SVM to deliver followers to their customers to distinguish between the real followers and benign website, analyzing the result from SVM, analyzing the factors that will help Twitter to keep its stabilized position if it reaches their goals for someone who have tons of followers. By SentiStrength and scoring manually, data that are used are tweets from NewFollow.com that being sorted by nodeXL. Tweets that have regained from nodeXL will be placed in pre-processing and continued into filtering data user account from twitter using SVM classification. The result that is obtained summarizes that twitter user are likely to have tons of real followers rather than the benign website to grow their social life status and business.
Keyword: twitter, online social networks, followers market, SVM, pyramid scheme

Subjek

ONLINE SOCIAL NETWORKS
 

Katalog

TWITTER FOLLOWERS ANALYSIS SENTIMENT WITH SUPPORT VECTOR MACHINE METHOD
 
 
Indonesia

Sirkulasi

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Tidak

Pengarang

TEGUH RAMADHANY
Perorangan
Erwin Budi Setiawan
 

Penerbit

Universitas Telkom
Bandung
2018

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  • IKG2F4 - ANALISIS DAN PERANCANGAN ALGORITMA
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