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Incorporating deep visual features into multiobjective based multi-view search results clustering
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In: Mitra, Sayantan, Hasanuzzaman, Mohammed orcid:0000-0003-1838-0091 , Saha, Sriparna and Way, Andy orcid:0000-0001-5736-5930 (2018) Incorporating deep visual features into multiobjective based multi-view search results clustering. In: 27th International Conference on Computational Linguistics, 20-26 Aug 2018, Santa Fe, NM, USA. (2018)
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Temporal orientation of tweets for predicting income of users
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In: Hasanuzzaman, Mohammed orcid:0000-0003-1838-0091 , Kamila, Sabyasachi, Kaur, Mandeep, Saha, Sriparna and Ekbal, Asif (2017) Temporal orientation of tweets for predicting income of users. In: 55th Annual Meeting of the Association for Computational Linguistics, 30 Jul - 4 Aug 2017, Vancouver, Canada. (2017)
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Abstract:
Automatically estimating a user’s socioeconomic profile from their language use in social media can significantly help social science research and various downstream applications ranging from business to politics. The current paper presents the first study where user cognitive structure is used to build a predictive model of income. In particular, we first develop a classifier using a weakly supervised learning framework to automatically time-tag tweets as past, present, or future. We quantify a user’s overall temporal orientation based on their distribution of tweets, and use it to build a predictive model of income. Our analysis uncovers a correlation between future temporal orientation and income. Finally, we measure the predictive power of future temporal orientation on income by performing regression.
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Keyword:
Machine translating
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URL: http://doras.dcu.ie/23373/
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