A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
Volume 5 Issue 1
Jan.  2018

IEEE/CAA Journal of Automatica Sinica

  • JCR Impact Factor: 11.8, Top 4% (SCI Q1)
    CiteScore: 23.5, Top 2% (Q1)
    Google Scholar h5-index: 77, TOP 5
Turn off MathJax
Article Contents
Xin Kang, Fuji Ren and Yunong Wu, "Exploring Latent Semantic Information for Textual Emotion Recognition in Blog Articles," IEEE/CAA J. Autom. Sinica, vol. 5, no. 1, pp. 204-216, Jan. 2018. doi: 10.1109/JAS.2017.7510421
Citation: Xin Kang, Fuji Ren and Yunong Wu, "Exploring Latent Semantic Information for Textual Emotion Recognition in Blog Articles," IEEE/CAA J. Autom. Sinica, vol. 5, no. 1, pp. 204-216, Jan. 2018. doi: 10.1109/JAS.2017.7510421

Exploring Latent Semantic Information for Textual Emotion Recognition in Blog Articles

doi: 10.1109/JAS.2017.7510421

the National Natural Science Foundation of China (NSFC) Key Program 61573094

Fundamental Research Funds for the Central Universities N140402001

More Information
  • Understanding people's emotions through natural language is a challenging task for intelligent systems based on Internet of Things (IoT). The major difficulty is caused by the lack of basic knowledge in emotion expressions with respect to a variety of real world contexts. In this paper, we propose a Bayesian inference method to explore the latent semantic dimensions as contextual information in natural language and to learn the knowledge of emotion expressions based on these semantic dimensions. Our method synchronously infers the latent semantic dimensions as topics in words and predicts the emotion labels in both word-level and document-level texts. The Bayesian inference results enable us to visualize the connection between words and emotions with respect to different semantic dimensions. And by further incorporating a corpus-level hierarchy in the document emotion distribution assumption, we could balance the document emotion recognition results and achieve even better word and document emotion predictions. Our experiment of the wordlevel and the document-level emotion predictions, based on a well-developed Chinese emotion corpus Ren-CECps, renders both higher accuracy and better robustness in the word-level and the document-level emotion predictions compared to the state-of-theart emotion prediction algorithms.


  • loading
  • [1]
    H. Gunes and B. Schuller, "Categorical and dimensional affect analysis in continuous input:Current trends and future directions, " Image Vision Comput., vol. 31, no. 2, pp. 120-136, Feb. 2013. https://www.sciencedirect.com/science/article/pii/S0262885612001084
    J.-C. Lin, C.-H. Wu, and W.-L. Wei, "Error weighted semi-coupled hidden Markov model for audio-visual emotion recognition, " IEEE Trans. Multimedia, vol. 14, no. 1, pp. 142-156, Feb. 2012. http://ieeexplore.ieee.org/document/6042338/
    S. Scherer, M. Glodek, G. Layher, M. Schels, M. Schmidt, T. Brosch, S. Tschechne, F. Schwenker, H. Neumann, and G. Palm, "A generic framework for the inference of user states in human computer interaction, " J. Multimodal User Interfaces, vol. 6, no. 3-4, pp. 117-141, Nov. 2012. doi: 10.1007/s12193-012-0093-9
    F. J. Ren, X. Kang, and C. Q. Quan, "Examining accumulated emotional traits in suicide blogs with an emotion topic model, " IEEE J. Biomed. Health Inform., vol. 20, no. 5, pp. 1384-1396, Sep. 2016. http://ieeexplore.ieee.org/document/7164237/
    H. Mo, J. Wang, X. Li, and Z. L. Wu, "Linguistic dynamic modeling and analysis of psychological health state using interval type-2 fuzzy sets, " IEEE/CAA J. Automat. Sin., vol. 2, no. 4, pp. 366-373, Oct. 2015. http://ieeexplore.ieee.org/document/7296531/
    L. Bylsma, B. H. Morris, and J. Rottenberg, "A meta-analysis of emotional reactivity in major depressive disorder, " Clin. Psychol. Rev., vol. 28, no. 4, pp. 676-691, Apr. 2008. https://www.sciencedirect.com/science/article/pii/S0272735807001626
    G. Domes, L. Schulze, and S. C. Herpertz, "Emotion recognition in borderline personality disorder-a review of the literature, " J. Pers. Disord., vol. 23, no. 1, pp. 6-19, Feb. 2009. doi: 10.1521/pedi.2009.23.1.6
    K. A. Lindquist, T. D. Wager, H. Kober, E. Bliss-Moreau, and L. F. Barrett, "The brain basis of emotion:a meta-analytic review, " Behav. Brain Sci., vol. 35, no. 3, pp. 121-143, Jun. 2012. http://www.kristenalindquist.com/journal-articles/the-brain-basis-of-emotion-a-meta-analytic-review-pdf
    J. T. Buhle, J. A. Silvers, T. D. Wager, R. Lopez, C. Onyemekwu, H. Kober, J. Weber, and K. N. Ochsner, "Cognitive reappraisal of emotion:a meta-analysis of human neuroimaging studies, " Cereb. Cortex, vol. 24, no. 11, pp. 2981-2990, Nov. 2014. http://www.psychologicalscience.org/video/cognitive-reappraisal-of-emotion-a-meta-analysis-of-human-neuroimaging-studies.html
    C. H. Yang, K. H. Y. Lin, and H. H. Chen, "Emotion classification using web blog corpora, " in Proc. IEEE/WIC/ACM Int. Conf. Web Intelligence, Fremont, CA, 2007, pp. 275-278. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4427100
    R. Tokuhisa, K. Inui, and Y. Matsumoto, "Emotion classification using massive examples extracted from the web, " in Proc. 22nd Int. Conf. Computational Linguistics, Manchester, United Kingdom, 2008, pp. 881-888. http://dl.acm.org/citation.cfm?id=1599192
    I. Maks and P. Vossen, "A verb lexicon model for deep sentiment analysis and opinion mining applications, " Proc. 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis, Portland, Oregon, USA, 2011, pp. 10-18. https://www.sciencedirect.com/science/article/pii/S0167923612001364
    S. M. Mohammad and T. Yang, "Tracking sentiment in mail:How genders differ on emotional axes, " Proc. 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis, Portland, Oregon, USA, 2011, pp. 70-79. http://adsabs.harvard.edu/abs/2013arXiv1309.6347M
    A. Balahur, J. M. Hermida, and A. Montoyo, "Detecting implicit expressions of emotion in text:A comparative analysis, " Decis. Support Syst., vol. 53, no. 4, pp. 742-753, Nov. 2012. https://www.sciencedirect.com/science/article/pii/S0167923612001352
    W. Y. Li and H. Xu, "Text-based emotion classification using emotion cause extraction, " Expert Syst. Appl., vol. 41, no. 4, pp. 1742-1749, Mar. 2014. https://www.sciencedirect.com/science/article/pii/S0957417413006945
    S. Matsumoto, H. Takamura, and M. Okumura, "Sentiment classification using word sub-sequences and dependency sub-trees, " in Advances in Knowledge Discovery and Data Mining, T. B. Ho, D. Cheung, and H. Liu, Eds. Hanoi, Vietnam:Springer, 2005, pp. 301-311. https://www.microsoft.com/en-us/research/publication/sentiment-classification-using-word-sub-sequences-and-dependency-sub-trees/
    T. Kudo and Y. Matsumoto, "A boosting algorithm for classification of semi-structured text. in Proc. 2004 Conf. Empirical Methods in Natural Language Processing, Barcelona, Spain, 2004, pp. 301-308. https://www.microsoft.com/en-us/research/publication/a-boosting-algorithm-for-classification-of-semi-structured-text/
    C. H. Yang, K. H. Y. Lin, and H. H. Chen, "Building emotion lexicon from weblog corpora, " in Proc. 45th Annu. Meeting of the ACL on Interactive Poster and Demonstration Sessions, Prague, Czech Republic, 2007, pp. 133-136. http://dl.acm.org/citation.cfm?doid=1557769.1557809
    N. Kobayashi, K. Inui, Y. Matsumoto, K. Tateishi, and T. Fukushima, "Collecting evaluative expressions for opinion extraction, " in Proc. 1st Int. Joint Conf. Natural Language Processing, Hainan Island, China, 2004, pp. 596-605. doi: 10.1007/978-3-540-30211-7_63
    H. Teramura, "Japanese syntax and meaning, " Kurosio Publishers, 1982.
    X. Hu, J. S. Downie, and A. F. Ehmann, "Lyric text mining in music mood classification, " in Proc. 10th Int. Society for Music Information Retrieval Conf., Kobe, Japan, 2009, pp. 411-416. https://experts.illinois.edu/en/publications/lyric-text-mining-in-music-mood-classification
    C. Strapparava and A. Valitutti, "WordNet-affect:an affective extension of wordNet, " in Proc. 4th Int. Conf. Language Resources and Evaluation, Lisbon, Portugal, 2004, pp. 1083-1086.
    P. Singh, "The public acquisition of commonsense knowledge, " in Proc. AAAI Spring Symposium:Acquiring (and Using) Linguistic (and World) Knowledge for Information Access, Palo Alto, CA, 2002. http://citeseerx.ist.psu.edu/viewdoc/bookmark?doi=
    H. Liu, H. Lieberman, and T. Selker, "A model of textual affect sensing using real-world knowledge, " in Proc. 8th Int. Conf. Intelligent User Interfaces, Miami, Florida, USA, 2003, pp. 125-132. http://dl.acm.org/citation.cfm?id=604067
    C. Q. Quan and F. J. Ren, "A blog emotion corpus for emotional expression analysis in Chinese, " Comput. Speech Lang., vol. 24, no. 4, pp. 726-749, Oct. 2010. http://cat.inist.fr/?aModele=afficheN&cpsidt=22702998
    S. Aman and S. Szpakowicz, "Identifying expressions of emotion in text, " in Text, Speech and Dialogue, V. Matoušek and P. Mautner, Eds. Pilsen, Czech Republic:Springer, 2007, pp. 196-205. doi: 10.1007/978-3-540-74628-7_27
    X. Kang, F. J. Ren, and Y. N. Wu, "Semisupervised learning of authorspecific emotions in micro-blogs, " IEEJ Trans. Electrical & Electronic Eng., vol. 11, no. 6, pp. 768-775, Nov. 2016. doi: 10.1002/tee.22302/full
    Y. N. Wu, K. Kita, F. J. Ren, K. Matsumoto, and X. Kang, "Modification relations based emotional keywords annotation using conditional random fields, " in Proc. 4th Int. Conf. Intelligent Networks and Intelligent Systems, Kunming, China, 2011, pp. 81-84. http://ieeexplore.ieee.org/document/6104698/
    Y. N. Wu, K. Kita, F. J. Ren, K. Matsumoto, and X. Kang, "Exploring emotional words for Chinese document chief emotion analysis, " in Proc. 25th Pacific Asia Conf. Language, Information and Computation, Singapore, 2011, pp. 597-606. https://core.ac.uk/display/46883906
    D. Das and S. Bandyopadhyay, "Word to sentence level emotion tagging for Bengali blogs, " in Proc. ACL-IJCNLP 2009 Conf. Short Papers, Suntec, Singapore, 2009, pp. 149-152.
    X. Kang, F. J. Ren, and Y. N. Wu, "Bottom up:Exploring word emotions for Chinese sentence chief sentiment classification, " in Proc. 2010 Int. Conf. Natural Language Processing and Knowledge Engineering (NLPKE), Beijing, China, 2010. http://ieeexplore.ieee.org/xpl/abstractKeywords.jsp?reload=true&arnumber=5587793&punumber%3D5583927
    X. Kang and F. J. Ren, "Sampling latent emotions and topics in a hierarchical Bayesian network, " in Proc. 20117th Int. Conf. Natural Language Processing and Knowledge Engineering (NLP-KE), Tokushima, 2011, pp. 37-42. http://ieeexplore.ieee.org/document/6138166/
    F. J. Ren and X. Kang, "Employing hierarchical Bayesian networks in simple and complex emotion topic analysis, " Comput. Speech Lang., vol. 27, no. 4, pp. 943-968, Jun. 2013. https://www.sciencedirect.com/science/article/pii/S0885230812000605


    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(7)  / Tables(5)

    Article Metrics

    Article views (1349) PDF downloads(56) Cited by()


    DownLoad:  Full-Size Img  PowerPoint