A Corpus-based Approach to Finding Happiness

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This paper discusses how to locate emotions.

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6 p.

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Liu, Hugo & Mihalcea, Rada, 1974- March 2006.

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This paper is part of the collection entitled: UNT Scholarly Works and was provided by UNT College of Engineering to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 134 times , with 7 in the last month . More information about this paper can be viewed below.

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Description

This paper discusses how to locate emotions.

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6 p.

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Copyright 2006 American Association for Artificial Intelligence (AAAI). All rights reserved. http://www.aaai.org

Abstract: What are the sources of happiness and sadness in everyday life? In this paper, the authors employ 'linguistic ethnography' to seek out where happiness lies in our everyday lives by considering a corpus of blogposts from the LiveJournal community annotated with happy and sad moods. By analyzing this corpus, the authors derive lists of happy and sad words and phrases annotated by their 'happiness factor'. Various semantic analyses performed with this wordlist reveal the happiness trajectory of a 24-day (3am and 9-10p are most happy), and a 7-day week (Wednesdays are saddest), and compare the socialness and human-centeredness of happy descriptions versus sad descriptions. The authors evaluate our corpus-based approach in a classification task and contrast our wordlist with emotionally-annotated wordlists produced by experimental focus groups. Having located happiness temporally and semantically within this corpus of everyday life, the paper concludes by offering a corpus-inspired livable recipe for happiness.

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  • American Association for Artificial Intelligence (AAAI) Spring Symposium on Computational Approaches to Weblogs, 2006, Standford, California, United States

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  • March 2006

Added to The UNT Digital Library

  • Jan. 31, 2011, 2:01 p.m.

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  • March 27, 2014, 11:43 a.m.

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Liu, Hugo & Mihalcea, Rada, 1974-. A Corpus-based Approach to Finding Happiness, paper, March 2006; (digital.library.unt.edu/ark:/67531/metadc30980/: accessed June 27, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT College of Engineering.