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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 Hits 1 – 20 of 50 1 Unsupervised sentiment analysis with emotional signals Xia Hu; Jiliang Tang; Huiji Gao... In: http://www.public.asu.edu/~xiahu/papers/www13.pdf (2013) BASE Show details 2 Informal Multilingual Multi-domain Sentiment Analysis Tadej Štajner; Inna Novalija; Dunja Mladenić In: http://www.informatica.si/PDF/37-4/13_Stajner - Informal multilingual multi-domain sentiment analysis.pdf (2013) BASE Show details 3 Computational Linguistics (2012)" The French Social Media Bank: a Treebank of Noisy User Generated Content Djamé Seddah; Benoit Sagot Marie C; Virginie Mouilleron... In: http://hal.inria.fr/docs/00/78/08/95/PDF/coling2012.pdf (2013) BASE Show details 4 A Pointillism Approach for Natural Language Processing of Social Media Peiyou Song; Anhei Shu; Anyu Zhou... In: http://www.cs.unm.edu/%7Ecrandall/64.pdf (2012) BASE Show details 5 Dealing with input noise in statistical machine translation.” COLING Lluis Formiga; Jose A. R. Fonollosa In: http://aclweb.org/anthology/C/C12/C12-2032.pdf (2012) BASE Show details 6 Informal language learning setting: Technology or social interaction? The Turkish Online Taher Bahrani; Tam Shu Sim In: http://www.tojet.net/articles/v11i2/11215.pdf (2012) BASE Show details 7 Mark my words! Linguistic style accommodation in social media Cristian Danescu-niculescu-mizil; Michael Gamon; Susan Dumais In: http://www.cs.cornell.edu/~cristian/papers/accommodation.pdf (2011) BASE Show details 8 Finding high-quality content in social media with an application to community-based question answering Eugene Agichtein; Aristides Gionis; Carlos Castillo... In: http://www.mathcs.emory.edu/~eugene/papers/wsdm2008quality.pdf (2008) BASE Show details 9 Privacy in Video Media Spaces Michael Boyle; Saul Greenberg In: http://grouplab.cpsc.ucalgary.ca/grouplab/uploads/Publications/Publications/2003-LexiconPrivacy.Report2003-724-27.pdf (2005) BASE Show details 10 Finding Romanized Arabic Dialect in Code-Mixed Tweets In: http://www.lrec-conf.org/proceedings/lrec2014/pdf/1116_Paper.pdf BASE Show details 11 Approaches, Tools and Applications for Sentiment Analysis Implementation Fernando Ferri; Patrizia Grifoni; Tiziana Guzzo In: http://www.ijcaonline.org/research/volume125/number3/dandrea-2015-ijca-905866.pdf BASE Show details 12 Two Database Resources for Processing Social Media English Text Eleanor Clark; Kenji Araki In: http://www.lrec-conf.org/proceedings/lrec2012/pdf/288_Paper.pdf BASE Show details 13 Spanish Knowledge Base Generation for Polarity Classification from Masses ABSTRACT Arturo Montejo-ráez; José M. Perea-ortega In: http://www2013.org/companion/p571.pdf BASE Show details 14 Unsupervised sentiment analysis with emotional signals Xia Hu; Jiliang Tang; Huiji Gao; Huan Liu In: http://www2013.org/proceedings/p607.pdf Abstract: The explosion of social media services presents a great opportunity to understand the sentiment of the public via analyzing its large-scale and opinion-rich data. In social media, it is easy to amass vast quantities of unlabeled data, but very costly to obtain sentiment labels, which makes unsupervised sentiment analysis essential for various applications. It is challenging for traditional lexicon-based unsupervised methods due to the fact that expressions in social media are unstructured, informal, and fast-evolving. Emoticons and product ratings are examples of emotional signals that are associated with sentiments expressed in posts or words. Inspired by the wide availability of emotional signals in social media, we propose to study the problem of unsupervised sentiment analysis with emotional signals. Inparticular,we investigate whether the signals can potentially help sentiment analysis by providing a unified way to model two main categories of emotional signals, i.e., emotion indication and emotion correlation. We further incorporate the signals into an unsupervised learning framework for sentiment analysis. In the experiment, we compare the proposed framework with the state-of-the-art methods on two Twitter datasets and empirically evaluate our proposed framework to gain a deep understanding of the effects of emotional signals. Keyword: Emoticon; Experimentation Keywords Emotional Signals; General Terms Algorithm; Performance; Sentiment Analysis; Social Correlation; Social Media; Twitter URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.401.8023 http://www2013.org/proceedings/p607.pdf BASE Hide details 15 Feel the Heat: Emotion Detection in Arabic Social Media Content Omneya Rabie; Christian Sturm In: http://sdiwc.net/digital-library/web-admin/upload-pdf/00001223.pdf BASE Show details 16 The Call Triangle: student, teacher and institution Facebook used in a German film project Vera Leier In: http://files.eric.ed.gov/fulltext/ED542419.pdf BASE Show details 17 Unsupervised sentiment analysis with emotional signals Xia Hu; Jiliang Tang; Huiji Gao... In: http://www.public.asu.edu/~xiahu/papers/www13.pdf BASE Show details 18 User Community Reconstruction using Sampled Microblogging Data Miki Enoki; Yohei Ikawa; Raymond Rudy In: http://www2012.wwwconference.org/proceedings/companion/p657.pdf BASE Show details 19 A Content-Based Analysis of Travellers ’ Social Media Associate Professor; Dr. Linda; S. L. Lai In: http://world-comp.org/p2011/EEE8401.pdf BASE Show details 20 Movement in Learning: Revitalizing the Classroom Marcus Van In: http://digitalcollections.sit.edu/cgi/viewcontent.cgi?article%3D1544%26context%3Dipp_collection BASE Show details Page: 1 2 3

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