<i>Teenstagram TimeFrame</i>: a visualization for Instagram time dataset from teen users (case study in Surabaya, Indonesia)

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

What is inside the mind of teenagers on Instagram?

Instagram is one of the most used social media with 45 million active users on each month. In Indonesia, the highest number of internet users is between the age of 13 34 years old. It shows that most of the new internet users are young people. In this research, we create a topic model for the Instagram caption of teenager users in Surabaya, Indonesia, using latent dirichlet allocation (LDA) method. By using pen and paper questionnaire, we collected total number of Instagram 494 valid accounts with 4,664 captions. The data were collected from January 2014 to June 2017. The process of modelling using LDA was performed by experimenting with a set of number of topics: 2, 3, 4 and 5. The two topics were selected because it has a small value of perplexity, which indicates that the model has a good level of conformity. The two topics represents two categories: school and relationship . It was found that the topic model was dominated by the relationship category