A Case Study and Qualitative Analysis of Simple Cross-lingual Opinion Mining

Gerhard Hagerer, Wing Sheung Leung, Qiaoxi Liu, Hannah Danner, Georg Groh

2021

Abstract

User-generated content from social media is produced in many languages, making it technically challenging to compare the discussed themes from one domain across different cultures and regions. It is relevant for domains in a globalized world, such as market research, where people from two nations and markets might have different requirements for a product. We propose a simple, modern, and effective method for building a single topic model with sentiment analysis capable of covering multiple languages simultanteously, based on a pre-trained state-of-the-art deep neural network for natural language understanding. To demonstrate its feasibility, we apply the model to newspaper articles and user comments of a specific domain, i.e., organic food products and related consumption behavior. The themes match across languages. Additionally, we obtain an high proportion of stable and domain-relevant topics, a meaningful relation between topics and their respective textual contents, and an interpretable representation for social media documents. Marketing can potentially benefit from our method, since it provides an easy-to-use means of addressing specific customer interests from different market regions around the globe. For reproducibility, we provide the code, data, and results of our studya. ahttps://github.com/apairofbigwings/cross-lingual-opinion-mining

Paper Citation

in Harvard Style

Hagerer G., Leung W., Liu Q., Danner H. and Groh G. (2021). A Case Study and Qualitative Analysis of Simple Cross-lingual Opinion Mining. In Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2021) - Volume 1: KDIR; ISBN 978-989-758-533-3, SciTePress, pages 17-26. DOI: 10.5220/0010649500003064

in Bibtex Style

@conference{kdir21,
author={Gerhard Hagerer and Wing Sheung Leung and Qiaoxi Liu and Hannah Danner and Georg Groh},
title={A Case Study and Qualitative Analysis of Simple Cross-lingual Opinion Mining},
booktitle={Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2021) - Volume 1: KDIR},
year={2021},
pages={17-26},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010649500003064},
isbn={978-989-758-533-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2021) - Volume 1: KDIR
TI - A Case Study and Qualitative Analysis of Simple Cross-lingual Opinion Mining
SN - 978-989-758-533-3
AU - Hagerer G.
AU - Leung W.
AU - Liu Q.
AU - Danner H.
AU - Groh G.
PY - 2021
SP - 17
EP - 26
DO - 10.5220/0010649500003064
PB - SciTePress