[Objective] By collecting and visualizing the sentiment information from bullet-screen comments, we can extract the emotion features and the trend of online videos.[Context] The visualized information of bullet-screen comments can be considered as sentiment tags. Based on these labels of online video, a new retrieval model focusing on comment emotion can be raised.[Methods] According to sentence level sentiment analysis, the study model of sentiment analysis towards bullet-screen comments is developed, including process of constructing sentiment word dictionary, extracting sentiment words and calculating weight value of comments based on time series.[Results] Analyzing tools of radar map, tag cloud and trend-curve diagram are utilized to present the outcome.[Conclusions] Sentiment analysis and visualization methods utilized in bullet-screen comments can provide a new approach to retrieve online videos.
郑飏飏, 徐健, 肖卓. 情感分析及可视化方法在网络视频弹幕数据分析中的应用[J]. 现代图书情报技术, 2015, 31(11): 82-90.
Zheng Yangyang, Xu Jian, Xiao Zhuo. Utilization of Sentiment Analysis and Visualization in Online Video Bullet-screen Comments. New Technology of Library and Information Service, DOI：10.11925/infotech.1003-3513.2015.11.12.
[1] AcFun弹幕视频网[DB/OL]. [2015-04-17]. http://www.acfun. tv/. (AcFun [DB/OL]. [2015-04-17]. http://www.acfun.tv/.)
[2] 哔哩哔哩弹幕视频网[DB/OL]. [2015-04-17]. http://www. bilibili.com/. (bilibili [DB/OL]. [2015-04-17]. http://www. bilibili.com/.)
[3] Pang B, Lee L. Thumbs up?: Sentiment Classification Using Machine Learning Techniques [C]. In: Proceedings of the Conference on Empirical Methods in NLP. Morristown: ACL, 2002: 79-86.
[4] 刘志明, 刘鲁. 基于机器学习的中文微博情感分类实证研究[J]. 计算机工程与应用, 2012, 48(1): 1-4. (Liu Zhiming, Liu Lu. Empirical Study of Sentiment Classification for Chinese Microblog Based on Machine Learning [J]. Computer Engineering and Applications, 2012, 48(1): 1-4.)
[5] Yu H, Hatzivassiloglou V. Towards Answering Opinion Questions: Separating Facts from Opinions and Identifying the Polarity of Opinion Sentences [C]. In: Proceedings of the Conference on Empirical Methods in NLP. Morristown: ACL, 2003:129-136.
[6] Hu M, Liu B. Mining and Summarizing Customer Reviews [C]. In: Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York: ACM, 2004:168-177.
[7] Kim S M, Hovy E. Determining the Sentiment of Opinions [C]. In:Proceedings of the 20th International Conference on Computational Linguistics. Morristown: ACL, 2004: 1367-1373.
[8] Yang S, Li S, Zheng L, et al. Emotion Mining Reasearch on Microblog [C]. In: Proceedings of the 1st IEEE Symposium on Web Society (SWS'09). 2009: 71-75.
[9] 徐琳宏, 林鸿飞, 赵晶. 情感语料库的构建和分析[J]. 中文信息学报, 2008, 22(1): 116-122. (Xu Linhong, Lin Hongfei, Zhao Jing. Construction and Analysis of Emotional Corpus [J]. Journal of Chinese Information Processing, 2008, 22(1): 116-122.)
[10] 刨丁解羊中文分词器v3.2 [K/OL]. [2015-04-17]. http://www. crsky.com/soft/22209.html. (Paodingjieyang Chinese Word Segmentation Machine [K/OL]. [2015-04-17]. http://www.crsky. com/soft/22209.html.)
[11] Rao D, Ravichandran D. Semi-Supervised Polarity Lexicon Induction [C]. In: Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics. Morristown: ACL, 2009: 675-682.
[12] 杜振雷. 面向微博短文本的情感分析研究[D]. 北京: 北京信息科技大学, 2013. (Du Zhenlei. Sentiment Analysis Towards Microblog Short Text [D]. Beijing: Beijing Information Science and Technology University, 2013.)
[13] 谢丽星, 周明, 孙茂松. 基于层次结构的多策略中文微博情感分析和特征抽取[J]. 中文信息学报, 2012, 26(1): 73-83. (Xie Lixing, Zhou Ming, Sun Maosong. Hierarchical Structure Based Hybrid Approach to Sentiment Analysis of Chinese Micro Blog and Its Feature Extraction [J]. Journal of Chinese Information Processing, 2012, 26(1): 73-83.)
[14] TagxeDo: 在线云词成像制作工具[K/OL]. [2015-04-17]. http:// www.tagxedo.com/. (TagxeDo [K/OL]. [2015-04-17]. http://www. tagxedo.com/.)
