TWITTER FOLLOWERS ANALYSIS SENTIMENT WITH SUPPORT VECTOR MACHINE METHOD

TEGUH RAMADHANY

Informasi Umum

Kode

18.04.286

Klasifikasi

302.302 85 - Online social networks

Jenis

Karya Ilmiah - Skripsi (S1) - Reference

Subjek

Online Social Networks

Dilihat

256 kali

Informasi Lainnya

Abstraksi

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