| 李冠,赵毅.基于在线评论的政府数据开放平台用户增量需求研究[J].数字图书馆论坛,2022,(12):37~46 |
| 基于在线评论的政府数据开放平台用户增量需求研究 |
| Research on User Incremental Demand of Government Data Open Platform Based on Online Comments |
| 投稿时间：2022-11-21 |
| DOI：10.3772/j.issn.1673-2286.2022.12.005 |
| 中文关键词: 政府数据开放平台；用户增量需求；主题挖掘；情感倾向；文本相似度；主题演进 |
| 英文关键词: Government Data Open Platform; User Incremental Demand; Topic Mining; Emotional Tendency; Text Similarity; Theme Evolution |
| 基金项目: |
| 作者 | 单位 | | 李冠 | 山东科技大学计算机科学与工程学院 | | 赵毅 | 山东科技大学计算机科学与工程学院 |
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| 中文摘要: |
| 深入研究政府数据开放平台用户需求特征，更有效地为用户提供数据服务，让开放数据创造更大的经济和社会价值具有重要意义。本文采集9个省（市、自治区）级政府数据开放平台的用户评论数据，首先运用LDA模型挖掘平台初建期和发展期用户需求主题，分析其需求热点；其次选取朴素贝叶斯算法研究用户需求主题的情感倾向；最后计算两个时期的平台用户需求主题相似度，揭示用户增量需求的动态演进路径。研究结果表明，“数据改进”“社会保障”“公共安全”等需求主题是用户持续关注的领域，其中“社会保障”主题的情感倾向概率为0.75，用户情感倾向积极，“数据改进”主题的情感倾向概率为0.22，用户情感倾向消极。本文研究平台用户需求主题、情感诉求以及需求变化，促进政府数据开放平台根据用户增量需求不断持续改进，为平台建设发展提供有力支持。 |
| 英文摘要: |
| It is of great significance to deeply study the characteristics of users’ needs of government data open platform, provide users with dataservices more effectively, and make open data create greater economic and social value. This thesis collects user comment data of nine provincial (municipal, autonomous region) government data open platforms. First, LDA model is used to mine user demand themes in the initial construction period and development period of the platform to analyze their demand hotspots. Second, naive Bayesian algorithm is selected to study the emotional orientation of user demand themes. Finally, the similarity of platform user demand themes in the two periods is calculated to reveal the dynamic evolution path of user incremental demand. The research results show that “data improvement”, “social security”, “public security” and other demand topics are areas of continuous concern for users. Among them, the emotional probability of “social security” topics is 0.75, the emotional tendency of users is positive, the emotional probability of “data improvement” topics is 0.22, and the emotional tendency of users is negative. This thesis studies the theme, emotional appeal and demand change of the platform users, promotes the continuous improvement of the government data open platform according to the incremental needs of users, and provides strong support for the construction and development of the platform. |
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