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Clustering student Instagram accounts using author-topic model

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posted on 2023-02-20, 16:03 authored by Nur Aini Rakhmawati, NF Faiz, Irmasari Hafidz, Indra Raditya, Pande Dinatha, Andrianto Suwignyo
This study proposes topic model to cluster a group of high school teenager's Instagram account in Surabaya, Indonesia by using the author-topic models method. We collect valid 235 Instagram accounts (133 female, 102 male students). We gather a total of 3,346 captions of Instagram posts from 18 senior high schools. We find topics that define their Instagram's post or caption; these seven topics are namely: feeling, Surabaya events, photography, artists, vacation, religion and music. Through the process, the lowest perplexity come from 90 iterations, which suggests six groups of topics. The six topics are concluded based on the lowest perplexity value and labelled according to the words included in the topic. The topic of photography discussed by six schools. Photography, artists and vacation are discussed by three schools, while feeling and religion and music are being discussed by two and one school respectively.

Funding

Institute for research and community services, Institut Teknologi Sepuluh Nopember Surabaya, Indonesia

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

International Journal of Business Intelligence and Data Mining

Volume

19

Issue

1

Pages

70 - 79

Publisher

Inderscience

Version

  • AM (Accepted Manuscript)

Rights holder

© Inderscience Enterprises Ltd

Publisher statement

This paper was accepted for publication in the journal International Journal of Business Intelligence and Data Mining and the definitive published version is available at https://doi.org/10.1504/IJBIDM.2021.115954

Publication date

2021-06-11

Copyright date

2021

ISSN

1743-8187

eISSN

1743-8195

Language

  • en

Depositor

Irma Hafidz. Deposit date: 18 February 2023

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