| 附加情感特征的在线问答社区信息质量自动化评价 |
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| 引用本文： | 姜雯,许鑫,武高峰.附加情感特征的在线问答社区信息质量自动化评价[J].图书情报工作,2015,59(4):100-105. |
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| 作者姓名： | 姜雯 许鑫 武高峰 |
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| 作者单位： | 1. 华东师范大学商学院信息学系 上海 200241;
2. 北京林业大学信息学院 北京 100083 |
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| 摘 要： | 目的/意义] 考察在线问答社区信息中的情感特征以及其对在线问答社区信息质量自动化评价的影响。方法/过程] 综合以往研究,提取Yahoo! Answers中的回答信息的文本特征、用户特征、时序特征等,并提出附加情感标注的回答特征,利用Weka机器学习的方法进行信息质量自动化分类预测。结果/结论] 结果显示,在线问答社区信息中具有一定的情感特征且情感特征的加入能够提高分类预测的准确率。
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| 关 键 词： | 信息质量评价 问答社区 机器学习 情感分析 |
| 收稿时间： | 2014-12-22 |
Online Q&A Community Automatically Information Quality Evaluation with Sentiment Feature |
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| Jiang Wen,Xu Xin,Wu Gaofeng.Online Q&A Community Automatically Information Quality Evaluation with Sentiment Feature[J].Library and Information Service,2015,59(4):100-105. |
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| Authors: | Jiang Wen Xu Xin Wu Gaofeng |
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| Institution: | 1. Department of InformationScience, Business School, East China Normal University, Shanghai 200241;
2. College of Information, Beijing Forestry University, Beijing 100083 |
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| Abstract: | Purpose/significance] To study the sentiment in online Q&A community and examine the effect of the sentimental features on online Q&A community information automatically quality evaluation.Method/process] This article synthesized the previous researches, extracted the text features, user features, sequence features etc. and put forward the feature with sentiment tagging, using Weka machine learning to automatically evaluate the information quality.Result/conclusion] The experiment result shows that the addition of sentiment feature can improve the classification prediction accuracy. |
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| Keywords: | information quality evaluation Q&A community machine learning sentiment analysis |
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