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Sentiment Analysis for Older People in Cross-Platform Instant Messaging Service

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Book cover Emerging Technologies for Education (SETE 2016)

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Abstract

The population of older people increases in many developed and developing countries, so that the overall structures of the populations has been changing. However, older people are one of the most disadvantaged and vulnerable groups for digital exclusion in this technocratic society. Therefore, in this article, we aims to predict the sentiments for older people when they use the cross-platform instance messaging service such as WeChat or WhatsApp. Specifically, we adopt semi-annotation approaches to obtaining their sentimental labels from the textual data in the cross-platform instance messaging service. Furthermore, we propose a lexical-based framework for predicting the sentimental labels. The findings give us insight to develop applications for the inclusion of older people in digital world.

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Notes

  1. 1.

    www.wechat.com.

  2. 2.

    www.whatsapp.com.

  3. 3.

    line.me.

  4. 4.

    An emoji is an ideogram which is embedded in an electronic message.

References

  1. Census and Statistics Department of Hong Kong. Thematic household survey report C Report No. 52 (2013)

    Google Scholar 

  2. Baccianella, S., Esuli, A., Sebastiani, F.: SentiWordNet 3.0: an enhanced lexical resource for sentiment analysis and opinion mining. In: LREC, vol. 10, pp. 2200–2204 (2010)

    Google Scholar 

  3. Berkowsky, R.W., Cotton, S.R., Yost, E.A., Winstead, V.P.: Attitudes towards and limitations to ICT use in assisted and independent living communities: findings from a specially-designed technological intervention. Educ. Gerontol. 39(11), 797–811 (2013)

    Article  Google Scholar 

  4. Boulton-Lewis, M.G., Buys, L., Lovie-Kitchin, J., Barnett, K., David, N.L.: Ageing, learning, and computer technology in Australia. Educ. Gerontol. 33(3), 253–270 (2007)

    Article  Google Scholar 

  5. Cattaneo, M., Malighetti, P., Spinelli, D.: The impact of university of the third age courses on ICT adoption. Comput. Hum. Behav. 63, 613–619 (2016)

    Article  Google Scholar 

  6. Davey, J.A.: Active ageing and education in mid and later life. Ageing Soc. 22(01), 95–113 (2002)

    Article  Google Scholar 

  7. Glorot, X., Bordes, A., Bengio, Y.: Domain adaptation for large-scale sentiment classification: a deep learning approach. In: Proceedings of the 28th International Conference on Machine Learning (ICML 2011), pp. 513–520 (2011)

    Google Scholar 

  8. Khvorostianov, N., Elias, N., Nimrod, G.: Without it I am nothing: the internet in the lives of older immigrants. New Media Soc. 14(4), 583–599 (2012)

    Article  Google Scholar 

  9. Koopman-Boyden, P.G., Reid, S.L.: Internet/e-mail usage and well-being among 65–84 year olds in New Zealand: policy implications. Educ. Gerontol. 35(11), 990–1007 (2009)

    Article  Google Scholar 

  10. Li, X., Xie, H., Rao, Y., Chen, Y., Liu, X., Huang, H., Wang, F.L.: Weighted multi-label classification model for sentiment analysis of online news. In: 2016 International Conference on Big Data and Smart Computing (BigComp), pp. 215–222. IEEE (2016)

    Google Scholar 

  11. Ng, H.T., Low, J.K.: Chinese part-of-speech tagging: one-at-a-time or all-at-once? Word-based or character-based? In: EMNLP, pp. 277–284 (2004)

    Google Scholar 

  12. Ortigosa, A., Martín, J.M., Carro, R.M.: Sentiment analysis in Facebook and its application to e-learning. Comput. Hum. Behav. 31, 527–541 (2014)

    Article  Google Scholar 

  13. Rao, Y., Xie, H., Li, J., Jin, F., Wang, L.F., Li, Q.: Social emotion classification of short text via topic-level maximum entropy model. Inf. Manag. 53(8), 978–986 (2016)

    Article  Google Scholar 

  14. Xie, H.-R., Li, Q., Cai, Y.: Community-aware resource profiling for personalized search in folksonomy. J. Comput. Sci. Technol. 27(3), 599–610 (2012)

    Article  MATH  Google Scholar 

  15. Xie, H., Li, Q., Mao, X.: Context-aware personalized search based on user and resource profiles in folksonomies. In: Sheng, Q.Z., Wang, G., Jensen, C.S., Xu, G. (eds.) APWeb 2012. LNCS, vol. 7235, pp. 97–108. Springer, Heidelberg (2012). doi:10.1007/978-3-642-29253-8_9

    Chapter  Google Scholar 

  16. Xie, H., Li, Q., Mao, X., Li, X., Cai, Y., Zheng, Q.: Mining latent user community for tag-based and content-based search in social media. Comput. J. 57(9), 1415–1430 (2014)

    Article  Google Scholar 

  17. Xie, H., Li, X., Wang, T., Chen, L., Li, K., Wang, F.L., Cai, Y., Li, Q., Min, H.: Personalized search for social media via dominating verbal context. Neurocomputing 172, 27–37 (2016)

    Article  Google Scholar 

  18. Xie, H., Li, X., Wang, T., Lau, R.Y.K., Wong, T.-L., Chen, L., Wang, F.L., Li, Q.: Incorporating sentiment into tag-based user profiles and resource profiles for personalized search in folksonomy. Inf. Process. Manag. 52(1), 61–72 (2016)

    Article  Google Scholar 

  19. Xie, H., Zou, D., Lau, R.Y.K., Wang, F.L., Wong, T.-L.: Generating incidental word-learning tasks via topic-based and load-based profiles. IEEE Multimedia 23(1), 60–70 (2016)

    Article  Google Scholar 

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Acknowledgement

The work described in this paper was fully supported by a grant from Research Grants Council of Hong Kong Special Administrative Region, China (UGC/FDS11/E06/14), the Internal Research Grant (RG 30/2014-2015) and the Start-Up Research Grant (RG 37/2016-2017R) of The Education University of Hong Kong.

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Correspondence to Di Zou .

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Xie, H., Wong, TL., Zou, D., Wang, F.L., Wong, L.P. (2017). Sentiment Analysis for Older People in Cross-Platform Instant Messaging Service. In: Wu, TT., Gennari, R., Huang, YM., Xie, H., Cao, Y. (eds) Emerging Technologies for Education. SETE 2016. Lecture Notes in Computer Science(), vol 10108. Springer, Cham. https://doi.org/10.1007/978-3-319-52836-6_30

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  • DOI: https://doi.org/10.1007/978-3-319-52836-6_30

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