Innovation in technology brings tremendous impact in various areas, including theissues of democracy, politics andgovernment. Inthisstudy, authorsobserve twitter as a digital medium to gather people from diverse background to communicate each other. Conversation in twitter, known as tweet, could be a gateto represent various political issues. This study aims to analyze valence and arousal of Indonesia's top political topics in twitter started from November 2015 until May 2016. Top political topics are collected with one primary keyword, jokowi. Each topic is represented with various tweets from different users. The data is collected by specializedcomputer software namely tracker developedby Provetic Lab. As an attempt to analyze tweets, authors used Algoritma Kata (AK) as the primary instrument toanalyze valence and arousal contained in each topic. Result shows when users talked about jokowi and kebanggaan (pride), theconversation contained positive valence and high excitement in arousal level. Whereas, when users discussed corruption and other scandal involving Government, the conversationturnedintonegativevalencewithdifferentarousallevel. Keywords: Computational psychology, jokowi,valence, arousal, politics ABSTRAKInovasi di bidang teknologi membawa dampak yang signifikan dalam berbagai area, termasukisudemokrasi, politik dan pemerintahan. Dalam studi ini, penulis memperhatikan twitter sebagai media digital yang mampu mempertemukan individu dari berbagai latar belakang untukmenjalin komunikasi. Percakapan di twitter, atauyang lebihawam dikenal sebagaitweet, dapat menjadi pintumasuk untuk memahami berbagai isu politik. Studi ini bertujuan untuk menganalisis valensi dan arousal dari topik-topik politik yang muncul di percakapan twitter. Topik-topikpolitik dikumpulkan dengan satu kata kunci, yaitu jokowi. Setiap topik direpresentasikan oleh berbagai tweet dari berbagai user. Data dikumpulkan melalui software khusus yang bernama tracker, dikembangkan oleh Provetic Lab. Sebagai usaha untuk menganalisis valensi dan arousal dari tweet di setiap topik, penulis menggunakan instrumen Algoritma Kata (AK). Hasil menunjukkan ketika 80user membicarakan jokowi dan topik kebanggaan (pride), percakapan memiliki muatan valensi positif dan tingkat arousal yang tinggi, sedangkan ketika user membicarakan mengenai korupsi (corruption) dan skandal lain yang melibatkan pemerintah, percakapan memiliki muatan valensi yang cenderung negatif dengan tingkat arousal yang berbedabeda.
Abstract. The ability to know emotional states for large number of people is important, for example, to ensure the effectiveness of public policies. In this study, we propose a measure of happiness that can be used in large scale population that is based on the analysis of Indonesian language lexicons. Here, we incorporate human assessment of Indonesian words, then quantify happiness on large-scale of texts gathered from twitter conversations. We used two psychological constructs to measure happiness: valence and arousal. We found that Indonesian words have tendency towards positive emotions. We also identified several happiness patterns during days of the week, hours of the day, and selected conversation topics.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.