Research on Demand Mining Method for Short Life Cycle Experiential Products Based on Structural Topic Model and Experience Value

Zhongjun Tang, Xinhao Zhou

2022

Abstract

With the development of social economy, short life cycle experiential products occupy an increasingly important position in the market. The demand for short life cycle experiential products through big data methods is of great significance to product improvement and innovation. This paper proposes a short-life cycle experience product demand mining method based on structural topic model and experience value. In order to meet the short-term characteristics of short life cycle experiential products, collect user comment data on the website, and adopt the structural topic model (STM) method, the user comment rating is used as the covariate in STM model, extract the customer demand topic words and their corresponding emotional tendencies and visualizing. The demand topics excavated using the STM method are divided into five categories based on the experience value theory, so that the excavated short life cycle experiential product demands are experiential. This paper takes a movie as an example to verify the effectiveness of the proposed method. The method is effective and more accurate than traditional methods, which provides guidance for enterprises to tap customer needs and product innovation.

Paper Citation

in Harvard Style

Tang Z. and Zhou X. (2022). Research on Demand Mining Method for Short Life Cycle Experiential Products Based on Structural Topic Model and Experience Value. In Proceedings of the 1st International Conference on Public Management, Digital Economy and Internet Technology - Volume 1: ICPDI; ISBN 978-989-758-620-0, SciTePress, pages 665-673. DOI: 10.5220/0011754200003607

in Bibtex Style

@conference{icpdi22,
author={Zhongjun Tang and Xinhao Zhou},
title={Research on Demand Mining Method for Short Life Cycle Experiential Products Based on Structural Topic Model and Experience Value},
booktitle={Proceedings of the 1st International Conference on Public Management, Digital Economy and Internet Technology - Volume 1: ICPDI},
year={2022},
pages={665-673},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011754200003607},
isbn={978-989-758-620-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Public Management, Digital Economy and Internet Technology - Volume 1: ICPDI
TI - Research on Demand Mining Method for Short Life Cycle Experiential Products Based on Structural Topic Model and Experience Value
SN - 978-989-758-620-0
AU - Tang Z.
AU - Zhou X.
PY - 2022
SP - 665
EP - 673
DO - 10.5220/0011754200003607
PB - SciTePress