loading
Documents

Research.Publish.Connect.

Paper

Authors: Diana Lopes-Teixeira 1 ; Fernando Batista 2 and Ricardo Ribeiro 2

Affiliations: 1 Instituto Universitário de Lisboa (ISCTE-IUL), Lisboa and Portugal ; 2 Instituto Universitário de Lisboa (ISCTE-IUL), Lisboa, Portugal, L2F, INESC-ID Lisboa, Lisboa and Portugal

ISBN: 978-989-758-330-8

Keyword(s): Topic Modeling, Topics Evolution, LDA, Preprocessing, Brand Interest.

Abstract: Topic Modeling is a well-known unsupervised learning technique used when dealing with text data. It is used to discover latent patterns, called topics, in a collection of documents (corpus). This technique provides a convenient way to retrieve information from unclassified and unstructured text. Topic Modeling tasks have been performed for tracking events/topics/trends in different domains such as academic, public health, marketing, news, and so on. In this paper, we propose a framework for extracting topics from a large dataset of short messages, for brand interest tracking purposes. The framework consists training LDA topic models for each brand using time intervals, and then applying the model on aggregated documents. Additionally, we present a set of preprocessing tasks that helped to improve the topic models and the corresponding outputs. The experiments demonstrate that topic modeling can successfully track people’s discussions on Social Networks even in massive datasets, and ca pture those topics spiked by real-life events. (More)

PDF ImageFull Text

Download
Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 54.87.61.215

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Lopes-Teixeira, D.; Batista, F. and Ribeiro, R. (2018). Discovering Trends in Brand Interest through Topic Models.In Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, ISBN 978-989-758-330-8, pages 245-252. DOI: 10.5220/0006936202450252

@conference{kdir18,
author={Diana Lopes{-}Teixeira. and Fernando Batista. and Ricardo Ribeiro.},
title={Discovering Trends in Brand Interest through Topic Models},
booktitle={Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR,},
year={2018},
pages={245-252},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006936202450252},
isbn={978-989-758-330-8},
}

TY - CONF

JO - Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR,
TI - Discovering Trends in Brand Interest through Topic Models
SN - 978-989-758-330-8
AU - Lopes-Teixeira, D.
AU - Batista, F.
AU - Ribeiro, R.
PY - 2018
SP - 245
EP - 252
DO - 10.5220/0006936202450252

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.