Teenstagram TimeFrame: A Visualization for Instagram Time Dataset from Teen Users (Case Study in Surabaya, Indonesia)

Irmasari Hafidz*, Alvin Rahman Kautsar, Tetha Valianta, Nur Aini Rakhmawati

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)

Abstract

The aim of this study is to create Teenstagram, a visualization for online pattern activity using Instagram dataset from teen users (junior high school, 7th-9th grade) in Surabaya, Indonesia. First, an offline workshop about ethics using Internet and social media for 18 junior high schools in Surabaya were conducted about three weeks, from 3rd until 26th October 2016. Second, we create Teenstagram, by building a web application to visualize and analyze the pattern activity from teen users using Instagram. We get the 290 Instagram users account from 579 students who fill in the survey from the first stage of the research. We employ K-Modes using R to cluster the dataset with six categorical features; online type activity (like, comment follow), days in the week (Monday-Sunday), hour (00-23), student activity (study time, rest time, school time), type of school (public and private activity), and sex (male, female). We propose a tool for analyzing Instagram dataset for online time activity, this result reveals the time pattern from the teen users using social media (e.g. Instagram) and what are the characteristics of each pattern has.

Original languageEnglish
Pages (from-to)100-107
Number of pages8
JournalProcedia Computer Science
Volume124
DOIs
Publication statusPublished - 2017
Event4th Information Systems International Conference 2017, ISICO 2017 - Bali, Indonesia
Duration: 6 Nov 20178 Nov 2017

Keywords

  • Categorical Attributes
  • Instagram
  • K-Modes
  • Online Behavior
  • R
  • Social Media
  • Teen
  • Visualization

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