工业工程

工业工程 ›› 2024, Vol. 27 ›› Issue (2): 74-86.doi: 10.3969/j.issn.1007-7375.230227

• 工业互联与制造服务管理 • 上一篇    下一篇

情感分析与数据驱动下面向产品迭代设计的用户画像及建模研究

周艳杰1, 李耀辉1, 王宇1, 王永胜2   

  1. 1. 郑州大学 管理学院，河南 郑州 450001;
    2. 中国烟草总公司郑州烟草研究院，河南 郑州 450001
  • 收稿日期:2023-12-05 发布日期:2024-04-29
  • 通讯作者: 王宇(1990-),男,河南省人,讲师,博士,主要研究方向为信息产品与服务管理、数字化平台运营、大数据治理。Email:ywang@zzu.edu.cn E-mail:ywang@zzu.edu.cn
  • 作者简介:周艳杰(1988-),男,河南省人,副研究员,博士,主要研究方向为启发式算法、组合优化、智能制造、智慧物流
  • 基金资助:
    国家自然科学基金资助项目 (72201252, 72101240)；郑州烟草研究院青年人才托举工程项目 (602020CR0360)

User Profiles and Modeling for Iterative Product Designing with Sentiment Analysis and Data-driven Approaches

ZHOU Yanjie1, LI Yaohui1, WANG Yu1, WANG Yongsheng2   

  1. 1. School of Management, Zhengzhou University, Zhengzhou 450001, China;
    2. Zhengzhou Tobacco Research Institute of China National Tobacco Corporation, Zhengzhou 450001, China
  • Received:2023-12-05 Published:2024-04-29

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摘要： 针对传统产品设计耗时耗力、效率较低等挑战，提出了面向产品迭代设计的用户画像及建模研究，该方法能够有效地刻画用户对产品特征的态度，为企业进行产品迭代提供新的参考模式。首先，通过爬虫技术获取用户信息属性、在线用户评论信息属性，结合产品信息属性构建三维用户画像概念模型。基于产品特征本体，采用Word2vec技术和情感分析方法从用户关注度和质量满意度两个维度构建画像模型。然后，通过整体用户画像与产品细粒度特征画像，聚焦产品核心优势特征与待优化特征，采用K值法制定产品优化策略。最后，以某相机为例进行数据驱动下的产品迭代设计案例分析。结果表明，该方法能够有效挖掘用户核心需求，为商家快速迭代产品提供较优产品设计方案。

关键词: 在线评论, 用户画像, 产品迭代, 数据驱动, 情感分析

Abstract: To address the issues of time-consuming and laborious, as well as low efficiency of traditional product designing, user profiles and a modeling method for iterative product designing is proposed. The proposed method can effectively capture use attitudes towards product features, providing a new baseline for enterprises to conduct product iteration. First, the user information attributes and online user comments are obtained by web crawler technology. A conceptual model of three-dimensional user profiles is established by integrating product information attributes. Based on product features, a profile model is developed using Word2vec technology and sentiment analysis from two dimensions: user attention and quality satisfaction. Then, by analyzing the overall user profile with the fine-grained feature profile of products, a product optimization strategy is determined using the K-value method, emphasizing both core advantageous features and features for optimization. Finally, a case study is conducted using a certain camera as an example to analyze data-driven iterative product designing. Results show that the proposed method can effectively explore the core demand of users and provide enhanced product design solutions for enterprises to expedite product iterations.

Key words: online comment, user profiles, product iteration, data-driven, sentiment analysis

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