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1
Unsupervised sentiment analysis with emotional signals
In: http://www.public.asu.edu/~xiahu/papers/www13.pdf (2013)
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2
Informal Multilingual Multi-domain Sentiment Analysis
In: http://www.informatica.si/PDF/37-4/13_Stajner - Informal multilingual multi-domain sentiment analysis.pdf (2013)
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3
Computational Linguistics (2012)" The French Social Media Bank: a Treebank of Noisy User Generated Content
In: http://hal.inria.fr/docs/00/78/08/95/PDF/coling2012.pdf (2013)
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4
A Pointillism Approach for Natural Language Processing of Social Media
In: http://www.cs.unm.edu/%7Ecrandall/64.pdf (2012)
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5
Dealing with input noise in statistical machine translation.” COLING
In: http://aclweb.org/anthology/C/C12/C12-2032.pdf (2012)
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6
Informal language learning setting: Technology or social interaction? The Turkish Online
In: http://www.tojet.net/articles/v11i2/11215.pdf (2012)
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7
Mark my words! Linguistic style accommodation in social media
In: http://www.cs.cornell.edu/~cristian/papers/accommodation.pdf (2011)
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8
Finding high-quality content in social media with an application to community-based question answering
In: http://www.mathcs.emory.edu/~eugene/papers/wsdm2008quality.pdf (2008)
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9
Privacy in Video Media Spaces
In: http://grouplab.cpsc.ucalgary.ca/grouplab/uploads/Publications/Publications/2003-LexiconPrivacy.Report2003-724-27.pdf (2005)
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10
Finding Romanized Arabic Dialect in Code-Mixed Tweets
In: http://www.lrec-conf.org/proceedings/lrec2014/pdf/1116_Paper.pdf
Abstract: Recent computational work on Arabic dialect identification has focused primarily on building and annotating corpora written in Arabic script. Arabic dialects however also appear written in Roman script, especially in social media. This paper describes our recent work developing tweet corpora and a token-level classifier that identifies a romanized Arabic dialect and distinguishes it from French and English in tweets. We focus on Moroccan Darija, one of several spoken vernaculars in the family of Maghrebi Arabic dialects. Even given noisy, code-mixed tweets, the classifier achieved token-level recall of 93.2 % on romanized Arabic dialect, 83.2 % on English, and 90.1 % on French. The classifier, now integrated into our tweet conversation annotation tool (Tratz et al. 2013), has semi-automated the construction of a romanized Arabic-dialect lexicon. Two datasets, a full list of Moroccan Darija surface token forms and a table of lexical entries derived from this list with spelling variants, as extracted from our tweet corpus collection, will be made available in the LRE MAP.
Keyword: Arabic dialect; code mixing; language identification; social media
URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.681.3705
http://www.lrec-conf.org/proceedings/lrec2014/pdf/1116_Paper.pdf
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11
Approaches, Tools and Applications for Sentiment Analysis Implementation
In: http://www.ijcaonline.org/research/volume125/number3/dandrea-2015-ijca-905866.pdf
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12
Two Database Resources for Processing Social Media English Text
In: http://www.lrec-conf.org/proceedings/lrec2012/pdf/288_Paper.pdf
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13
Spanish Knowledge Base Generation for Polarity Classification from Masses ABSTRACT
In: http://www2013.org/companion/p571.pdf
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14
Unsupervised sentiment analysis with emotional signals
In: http://www2013.org/proceedings/p607.pdf
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15
Feel the Heat: Emotion Detection in Arabic Social Media Content
In: http://sdiwc.net/digital-library/web-admin/upload-pdf/00001223.pdf
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16
The Call Triangle: student, teacher and institution Facebook used in a German film project
In: http://files.eric.ed.gov/fulltext/ED542419.pdf
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17
Unsupervised sentiment analysis with emotional signals
In: http://www.public.asu.edu/~xiahu/papers/www13.pdf
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18
User Community Reconstruction using Sampled Microblogging Data
In: http://www2012.wwwconference.org/proceedings/companion/p657.pdf
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19
A Content-Based Analysis of Travellers ’ Social Media
In: http://world-comp.org/p2011/EEE8401.pdf
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20
Movement in Learning: Revitalizing the Classroom
In: http://digitalcollections.sit.edu/cgi/viewcontent.cgi?article%3D1544%26context%3Dipp_collection
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