基于社会化问答社区涌现模式分析的领域热点识别研究

doi:10.3772/j.issn.1000-0135.2021.02.011

情报学报

2021, Vol. 40

Issue (2): 213-222 DOI: 10.3772/j.issn.1000-0135.2021.02.011

情报用户与行为研究

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基于社会化问答社区涌现模式分析的领域热点识别研究

于晶

华东师范大学政治学系，上海 200241

Detection of Hotspot in Scientific Fields Based on Emerging Pattern Analysis of Social Q&A Community Contents

Yu Jing

Department of Politics, East China Normal University, Shanghai 200241

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摘要领域热点识别是科技情报与文献计量领域研究的关键问题之一，其能够为科技、教育部门的政策制定及科研人员的研究决策提供参考和依据。现有领域热点识别的研究主要基于文献计量学方法，并没有利用丰富的Web数据。本文提出了一种基于涌现模式挖掘的框架，利用社会化问答社区中的问答内容来识别领域研究热点。首先，提取问答内容中的关键词，并基于关键词的共现性进行聚类；然后，基于聚类结果构建候选研究热点模式集合，利用涌现模式挖掘方法识别领域研究热点并分析其发展趋势。本文基于知乎社区的“机器学习”话题数据集进行实验，利用卡方检验与领域前沿进行对比，结果表明该框架能够有效识别领域研究热点。该方法利用关键词聚类较好的缓解了涌现模式识别方法计算复杂度大等问题，具有良好的可行性；同时，该方法在线社区热点识别等问题中具有潜在的应用价值。

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	于晶

关键词 ：领域热点识别, 涌现模式挖掘, 热点趋势分析, 社会化问答社区

收稿日期: 2020-01-10

基金资助:教育部人文社会科学研究项目“舆情生态治理下政务新媒体运营策略与传播效果研究——以省级行政机构为例”（17YJA860022）。

作者简介: 于晶，女，1981年生，博士，副教授，硕士生导师，主要研究方向为社交媒体分析，E-mail: jyu@dlps.ecnu.edu.c；

引用本文:

于晶. 基于社会化问答社区涌现模式分析的领域热点识别研究[J]. 情报学报, 2021, 40(2): 213-222.
Yu Jing. Detection of Hotspot in Scientific Fields Based on Emerging Pattern Analysis of Social Q&A Community Contents. 情报学报, 2021, 40(2): 213-222.

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https://qbxb.istic.ac.cn/CN/10.3772/j.issn.1000-0135.2021.02.011 或 https://qbxb.istic.ac.cn/CN/Y2021/V40/I2/213

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