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Unsupervised sentiment analysis with emotional signals
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In: http://www.public.asu.edu/~xiahu/papers/www13.pdf (2013)
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Informal Multilingual Multi-domain Sentiment Analysis
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In: http://www.informatica.si/PDF/37-4/13_Stajner - Informal multilingual multi-domain sentiment analysis.pdf (2013)
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Computational Linguistics (2012)" The French Social Media Bank: a Treebank of Noisy User Generated Content
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In: http://hal.inria.fr/docs/00/78/08/95/PDF/coling2012.pdf (2013)
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A Pointillism Approach for Natural Language Processing of Social Media
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In: http://www.cs.unm.edu/%7Ecrandall/64.pdf (2012)
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Dealing with input noise in statistical machine translation.” COLING
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In: http://aclweb.org/anthology/C/C12/C12-2032.pdf (2012)
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Mark my words! Linguistic style accommodation in social media
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In: http://www.cs.cornell.edu/~cristian/papers/accommodation.pdf (2011)
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Finding high-quality content in social media with an application to community-based question answering
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In: http://www.mathcs.emory.edu/~eugene/papers/wsdm2008quality.pdf (2008)
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Finding Romanized Arabic Dialect in Code-Mixed Tweets
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In: http://www.lrec-conf.org/proceedings/lrec2014/pdf/1116_Paper.pdf
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Approaches, Tools and Applications for Sentiment Analysis Implementation
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In: http://www.ijcaonline.org/research/volume125/number3/dandrea-2015-ijca-905866.pdf
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| 10 |
Two Database Resources for Processing Social Media English Text
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In: http://www.lrec-conf.org/proceedings/lrec2012/pdf/288_Paper.pdf
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Abstract:
This research focuses on text processing in the sphere of English-language social media. We introduce two database resources. The first, CECS (Casual English Conversion System) database, a lexicon-type resource of 1,255 entries, was constructed for use in our experimental system for the automated normalization of casual, irregularly-formed English used in communications such as Twitter. Our rule-based approach primarily aims to avoid problems caused by user creativity and individuality of language when Twitter-style text is used as input in Machine Translation, and to aid comprehension for non-native speakers of English. Although the database is still under development, we have so far carried out two evaluation experiments using our system which have shown positive results. The second database, CEGS (Casual English Generation System) phoneme database contains sets of alternative spellings for the phonemes in the CMU Pronouncing Dictionary, designed for use in a system for generating phoneme-based casual English text from regular English input; in other words, automatically producing humanlike creative sentences as an AI task. This paper provides an overview of the necessity, method, application and evaluation of both resources.
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Keyword:
Natural Language Processing; Social Media; Text Normalization
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URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.672.1500
http://www.lrec-conf.org/proceedings/lrec2012/pdf/288_Paper.pdf
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| 11 |
Spanish Knowledge Base Generation for Polarity Classification from Masses ABSTRACT
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In: http://www2013.org/companion/p571.pdf
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| 12 |
Unsupervised sentiment analysis with emotional signals
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In: http://www2013.org/proceedings/p607.pdf
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| 13 |
Feel the Heat: Emotion Detection in Arabic Social Media Content
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In: http://sdiwc.net/digital-library/web-admin/upload-pdf/00001223.pdf
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| 14 |
The Call Triangle: student, teacher and institution Facebook used in a German film project
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In: http://files.eric.ed.gov/fulltext/ED542419.pdf
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| 15 |
Unsupervised sentiment analysis with emotional signals
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In: http://www.public.asu.edu/~xiahu/papers/www13.pdf
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User Community Reconstruction using Sampled Microblogging Data
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In: http://www2012.wwwconference.org/proceedings/companion/p657.pdf
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A Content-Based Analysis of Travellers ’ Social Media
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In: http://world-comp.org/p2011/EEE8401.pdf
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| 18 |
Named Entity Trends Originating from Social Media
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In: http://www.aclweb.org/anthology/W/W12/W12-5501.pdf
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| 19 |
Mark My Words! Linguistic Style Accommodation in Social Media
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In: http://www.www2011india.com/proceeding/proceedings/p745.pdf
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| 20 |
Visualising Topical Sentiment in Twitter Streams
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In: http://oak.dcs.shef.ac.uk/smile2013/smile2013_paper2.pdf
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