Sarcasm Recognition


Notes:

  • Computational irony

Resources:

References:

See also:

Computational HumorSentiment Analysis & Dialog Systems


From humor recognition to irony detection: The figurative language of social media A Reyes, P Rosso, D Buscaldi – Data & Knowledge Engineering, 2012 – Elsevier … regarding irony. Keywords. Humor recognition; Irony detection; Natural language processing; Web text analysis. 1. Introduction. Figurative language is one of the most arduous topics facing Natural Language Processing (NLP). Unlike … Cited by 30 Related articles All 4 versions

Users’ Sentiment Analysis in Social Media Context using Natural Language Processing N Bhardwaj, A Shukla, P Swarnakar – The International Conference on …, 2014 – sdiwc.net … This can be tackled with the parameter “Num_of_likes”. The other challenge is “Sarcasm detection” which can be dealt by ruling out the variations or higher degree of disparity. The results analyzed using this natural language processing toolkit has been discussed below. …

Semi-supervised recognition of sarcastic sentences in twitter and amazon D Davidov, O Tsur, A Rappoport – … on Computational Natural Language …, 2010 – dl.acm.org Proceedings of the Fourteenth Conference on Computational Natural Language Learning, pages 107–116, Uppsala, Sweden, 15-16 July 2010. … In this paper we experiment with semi- supervised sarcasm identification on two very different data sets: a collection of 5.9 million … Cited by 87 Related articles All 20 versions

Mining subjective knowledge from customer reviews: a specific case of irony detection A Reyes, P Rosso – Proceedings of the 2nd Workshop on Computational …, 2011 – dl.acm.org … A Specific Case of Irony Detection Antonio Reyes and Paolo Rosso Natural Language Engineering Lab – ELiRF Departamento de Sistemas Informáticos y Computación Universidad Politécnica de Valencia, Spain {areyes,prosso}@dsic.upv.es Abstract … Cited by 17 Related articles All 7 versions

Building Corpora for Figurative Language Processing: The Case of Irony Detection A Reyes, P Rosso – … of the 4th International Workshop on …, 2012 – repository.dlsi.ua.es … The Case of Irony Detection Antonio Reyes1 2, Paolo Rosso2 1 Language Technology Lab Instituto Superior de Intérpretes y Traductores, Mexico antonioreyes@isit.edu.mx 2 Natural Language Engineering Lab — ELiRF Universitat Politècnica de València, Spain prosso@dsic … Cited by 2 Related articles All 2 versions

Identifying sarcasm in Twitter: a closer look R González-Ibáñez, S Muresan… – Proceedings of the 49th …, 2011 – dl.acm.org … To get a better sense of how difficult the task of sarcasm identification really is, we conducted three studies with human … Semi- Supervised Recognition of Sarcastic Sentences in Twitter and Amazon, Dmitry Proceeding of Compu- tational Natural Language Learning (ACL-CoNLL … Cited by 77 Related articles All 8 versions

An Impact Analysis of Features in a Classification Approach to Irony Detection in Product Reviews K Buschmeier, P Cimiano, R Klinger – 2014 – roman-klinger.de … 6The system as implemented to perform the described experiments is made available at https://github.com/ kbuschme/irony-detection/ … mturk.com/mturk/, accessed on March 10, 2014 9Using the TreeBankWordTokenizer as implemented in the Natural Language Toolkit (NLTK … Related articles All 2 versions

ICWSM-A Great Catchy Name: Semi-Supervised Recognition of Sarcastic Sentences in Online Product Reviews. O Tsur, D Davidov, A Rappoport – ICWSM, 2010 – aaai.org … In this paper we present SASI, a novel Semi-supervised Algorithm for Sarcasm Identification. … its linguistic and psychologic aspects (Muecke 1982; Stingfel- low 1994; Gibbs and Colston 2007), automatic recogni- tion of sarcasm is a novel task in natural language process- ing … Cited by 87 Related articles All 24 versions

Developing corpora for sentiment analysis and opinion mining: the case of irony and senti-tut C Bosco, V Patti, A Bolioli – IEEE Intelligent Systems, 2013 – computer.org … 3–16, 2012. [9] A. Reyes, P. Rosso, and D. Buscaldi, “From humor recognition to irony detection: The figurative … [11] A. Wang, C. Hoang, and MY Kan, “Perspectives on crowd-sourcing annotations for natural language processing,” Language Resources and Evaluation, vol. … Cited by 21 Related articles All 8 versions

Making objective decisions from subjective data: Detecting irony in customer reviews A Reyes, P Rosso – Decision Support Systems, 2012 – Elsevier … Keywords. Irony detection; Natural language processing; Web text analysis. 1. Introduction. Verbal communication is not a trivial process. It implies sharing a common code as well as being able to infer information beyond the semantic meaning. … Cited by 25 Related articles All 6 versions

Some clues on irony detection in tweets AA Vanin, LA Freitas, R Vieira… – Proceedings of the 22nd …, 2013 – dl.acm.org … Marco N. Bochernitsan PUCRS, FACIN Porto Alegre, RS, Brazil marco.bochernitsan@acad.pucrs. br Categories and Subject Descriptors I.2.7 [Artificial Intelligence]: Natural Language Process- ing General Terms Languages, Theory Keywords Microposts, Twitter, irony detection … Cited by 2 Related articles All 5 versions

Subjectivity and sentiment analysis: An overview of the current state of the area and envisaged developments A Montoyo, P Martínez-Barco, A Balahur – Decision Support Systems, 2012 – Elsevier … in Natural Language Processing (NLP) — the Artificial Intelligence (AI) discipline that deals with the automatic treatment of natural language in text … Finally, the paper presents different experiments in irony detection, based on the created corpus and the insights obtained through … Cited by 27 Related articles All 5 versions

Irony and Sarcasm: Corpus Generation and Analysis Using Crowdsourcing. E Filatova – LREC, 2012 – storm.cis.fordham.edu … The ability to reliably identify sarcasm and irony in text can improve the performance of many Natural Language Processing (NLP) systems including summarization, sentiment analysis, etc. The existing sarcasm detection systems have focused on identifying sarcasm on a … Cited by 14 Related articles All 3 versions

Pathways for irony detection in tweets LA de Freitas, AA Vanin, DN Hogetop… – Proceedings of the 29th …, 2014 – dl.acm.org … that detecting ironic senses repre- sent a big challenge for Natural Language Processing. By observing a corpus constitued by tweets, we propose a set of patterns that might suggest ironic/sarcastic statements. Thus, we developed special clues for irony detection, through the …

Really? well. apparently bootstrapping improves the performance of sarcasm and nastiness classifiers for online dialogue S Lukin, M Walker – NAACL 2013, 2013 – csctec-tsh.kdis.edu.cn … In Proc. of the Fourteenth Conference on Computational Natural Language Learning, p. 107– 116. Association for Computational Linguistics. … A. Reyes and P. Rosso. 2011. Mining subjective knowl- edge from customer reviews: a specific case of irony detection. In Proc. … Cited by 6 Related articles All 10 versions

Distinguishing Sarcasm From Literal Language: Evidence From Books and Blogging D Kovaz, RJ Kreuz, MA Riordan – Discourse Processes, 2013 – Taylor & Francis … of the 14th Conference on Computational Natural Language Learning, 107–116. Uppsala, Sweden. Association for Computational Linguistics. View all references) used Twitter to collect a large corpus containing such messages to test an algorithm for sarcasm recognition. … Cited by 1 Related articles All 2 versions

Extracting relevant knowledge for the detection of sarcasm and nastiness in the social web R Justo, T Corcoran, SM Lukin, M Walker… – Knowledge-Based …, 2014 – Elsevier … Our results show that the sarcasm detection task benefits from the inclusion of linguistic and semantic information sources, while nasty language is … is very different than the newspaper articles or task-oriented dialogs typically studied in work on natural language processing [33 …

A multidimensional approach for detecting irony in twitter A Reyes, P Rosso, T Veale – Language Resources and Evaluation, 2013 – Springer … Antonio Reyes 1 , Paolo Rosso 1 and Tony Veale 2. (1) Natural Language Engineering Lab, ELiRF, Universidad Politécnica de Valencia, Valencia, Spain. … As our media increasingly become more social, the problem of irony detection will become even more pressing. … Cited by 29 Related articles All 9 versions

Predicting Elections from Social Networks Based on Sub-event Detection and Sentiment Analysis S Unankard, X Li, M Sharaf, J Zhong, X Li – Web Information Systems …, 2014 – Springer … Given a message, the tasks are divided into three steps: word-level sentiment, aspect-level sentiment and sarcasm identification. … In order to detect a phrase, we applied natural language rules which are shown in Table 1. In this step, it is important to deal with complex linguistic …

A survey on the role of negation in sentiment analysis M Wiegand, A Balahur, B Roth, D Klakow… – … in natural language …, 2010 – dl.acm.org … It is important to make the distinction between subjectivity detec- tion and sentiment analysis, as they are two sep- arate tasks in natural language processing. … 66 Page 8. A data-driven approach for irony detection on product-reviews is presented in (Tsur et al., 2010). … Cited by 62 Related articles All 13 versions

Ontology based feature level opinion mining for portuguese reviews LA Freitas, R Vieira – Proceedings of the 22nd international conference …, 2013 – dl.acm.org … It is important to mention that, although natural language processing have a long history, little research had been done about opinion text before 2000 [7]. Nowadays … At last, we will apply a set of linguistic rules, such as: negatives, intensifiers [9] and irony/sarcasm detection. … Cited by 6 Related articles All 5 versions

Who cares about sarcastic tweets? investigating the impact of sarcasm on sentiment analysis D Maynard, MA Greenwood – Proceedings of LREC, 2014 – lrec-conf.org … Davidov et al. (Davidov et al., 2010) use Tsur’s algorithm for sarcasm detection, and achieve 82.7% F1 on tweets and 78.8% on Amazon re- views. … In Proceedings of the Fourteenth Conference on Computational Natural Language Learn- ing, pages 107–116. … Cited by 5 Related articles All 2 versions

Indonesian social media sentiment analysis with sarcasm detection E Lunando, A Purwarianti – Advanced Computer Science and …, 2013 – ieeexplore.ieee.org … The results in Table 3 showed that the additional features are effective in sarcasm detection. … Thumb’s up? Sentiment Classification using machine learning Techniques. Proceeding of the 7th Conference on Empirical Methods in Natural Language Processing (EMNLP-02). … Related articles

Linguistic-based patterns for figurative language processing: the case of humor recognition and irony detection AR Pérez – 2012 – dialnet.unirioja.es Linguistic-based Patterns for Figurative Language Processing: The Case of Humor Recognition and Irony Detection Antonio Reyes Pérez … Figurative language represents one of the most difficult tasks regard- ing natural language processing. Unlike literal language, figurative … Cited by 1 Related articles All 9 versions

Sarcasm as Contrast between a Positive Sentiment and Negative Situation. E Riloff, A Qadir, P Surve, L De Silva, N Gilbert… – EMNLP, 2013 – cs.utah.edu … González-Ibá˜nez et al. (2011) explored the usefulness of lexical and pragmatic fea- tures for sarcasm detection in tweets. They used sar- casm hashtags as gold labels. … Table 2: Experimental results on the test set lexicons could be for sarcasm recognition in tweets. … Cited by 4 Related articles All 4 versions

Towards Tracking Political Sentiment through Microblog Data Y Wang, T Clark, E Agichtein, J Staton – ACL 2014, 2014 – anthology.aclweb.org … 2009. Opinion Graphs for Po- larity and Discourse Classification. TextGraphs- 4: Graph-based Methods for Natural Language Pro- cessing. Aline A. Vanin, Larissa A. Freitas, Re-nata Vieira, and Marco Bochernitsan. 2013. Some clues on irony detection in tweets. …

Computational irony: A survey and new perspectives BC Wallace – Artificial Intelligence Review, 2013 – Springer … Recently, computationally detecting irony has attracted attention from the natural language processing (NLP) and machine learning (ML) communities. … Irony detection is an interesting machine learning problem because, in contrast to most text classi- fication tasks, it requires a … Cited by 4 Related articles

Annotating irony in a novel italian corpus for sentiment analysis A Gianti, C Bosco, V Patti, A Bolioli… – Proceedings of the 4th …, 2012 – di.unito.it … In absence of irony recognition, such tweet it is classified as positive, while it clearly expresses a criticism wrt the Rome’s mayor ability … This treebank is a freely available resource developed by the Natural Language Pro- cessing group of the University of Turin (for more details … Cited by 1 Related articles

On the difficulty of automatically detecting irony: beyond a simple case of negation A Reyes, P Rosso – Knowledge and Information Systems, 2013 – Springer … Keywords Irony detection · Negation · Figurative language processing 1 Introduction … P. Rosso Natural Language Engineering Lab, ELIRF, DSIC, Universitat Politècnica de València, Valencia, Spain 123 Page 2. A. Reyes, P. Rosso … Cited by 5 Related articles

Combining social cognitive theories with linguistic features for multi-genre sentiment analysis H Li, Y Chen, H Ji, S Muresan, D Zheng – Proceedings of the Pacific Asia …, 2012 – aclweb.org … Sarcasm Detection. For both tweets and forum posts, some remaining errors require accurate detec- tion of sarcasm (Davidov et al., 2010; Gonzalez- Ibanez et al., 2011). … In Pro- ceedings of the 2010 Conference on Empirical Meth- ods in Natural Language Processing. … Cited by 7 Related articles All 5 versions

Modelling Sarcasm in Twitter, a Novel Approach F Barbieri, H Saggion, F Ronzano – ACL 2014, 2014 – acl2014.org … In Section 3 we describes the corpus and text pro- cessing tools used and in Section 4 we present our approach to tackle the sarcasm detection prob- lem. … In Pro- ceedings of the International Conference on Recent Advances in Natural Language Processing. …

Sentiment analysis in twitter E Martínez-Cámara… – Natural Language …, 2014 – Cambridge Univ Press Page 1. Natural Language Engineering 20 (1): 1–28. … SA is framed within the area of natural language processing (NLP), and can be defined as the computational treatment of opinions, feelings and subjectivity in texts (Pang and Lee 2008). … Cited by 14 Related articles All 3 versions

Should I Care about Your Opinion? Detection of Opinion Interestingness and Dynamics in Social Media D Maynard, G Gossen, A Funk, M Fisichella – Future Internet, 2014 – mdpi.com … content, eg, [16–19]. It appears that none of these approaches go beyond this step of sarcasm detection: … sentiment expressed. In this paper, we do not describe in detail our work on sarcasm detection, but details can be found in [20]. Page 4. Future Internet 2014, 6 460 …

Twitter hashtags: Joint Translation and Clustering S Carter, M Tsagkias, W Weerkamp – Proceedings of the ACM WebSci’ …, 2011 – scarter.org … 2. RELATED WORK The use of tags has been examined for standard natural language processing tasks, such as supervised sentiment classification [1] and sarcasm detection [2], event detection [10, 11], and informa- tion diffusion [7, 9]. However, as well as using them as … Cited by 11 Related articles All 12 versions

Bootstrapped Learning of Emotion Hashtags #hashtags4you A Qadir, E Riloff – WASSA 2013, 2013 – aclweb.org … on sentiment analysis (Kouloumpis et al., 2011), emotion classification and lexicon generation (Mohammad, 2012), and sarcasm detection (Davi- dov et al … Identifying the emotion conveyed by a hashtag has not yet been studied by the natural language pro- cessing community. … Cited by 4 Related articles All 6 versions

Multimodal Sentiment Analysis of Social Media D Maynard, D Dupplaw, J Hare – 2013 – eprints.soton.ac.uk … Future work includes further development of the opinion mining tools: we have already begun investigations into issues such as sarcasm detection, more intricate use of … In: Proceedings of the International Conference on Recent Advances in Natural Language Processing. … Cited by 3 Related articles All 7 versions

Polarity detection of sarcastic political tweets DK Tayal, S Yadav, K Gupta, B Rajput… – … for Sustainable Global …, 2014 – ieeexplore.ieee.org … Polarity Detection Sarcasm Identification ~Output POS Tagger Data sets 625 … In future, efficiency and accuracy of an algorithm can further be increased by using Natural Language Processing more appropriately by considering the n-gram feature based dictionary. …

Neural substrates of irony comprehension: A functional MRI study M Shibata, A Toyomura, H Itoh, J Abe – Brain research, 2010 – Elsevier … Their findings indicated that sarcasm detection (sarcastic and non-sarcastic sentences contrasted with unconnected sentences) activated the neural circuits involved in mentalizing processes, as well as those of the semantic executive system. … Cited by 36 Related articles All 6 versions

On the Identification of Humor Markers in Computer-Mediated Communication. AC Adams – AAAI Fall Symposium: Artificial Intelligence of Humor, 2012 – aaai.org … Hancock (2004) examined irony recognition in face-to-face and CMC settings and found that amplifiers, ellipsis, and emoticons served as cues for … ordered by frequency could aid in the iden- tification of humor in future corpora, as well as benefit natural language processing at … Related articles All 2 versions

A faceted characterization of the opinion mining landscape, S Srinivasa – Communication Systems and Networks ( …, 2014 – ieeexplore.ieee.org … V. SARCASM DETECTION Sarcasm and irony are difficult verbal behaviors and many people who attempt to use them, fail to accomplish their task. … [14] Bing Liu. Sentiment analysis and subjectivity. In Handbook of Natural Language Processing, Second Edition. … Related articles

Modelling Irony in Twitter F Barbieri, H Saggion – EACL 2014, 2014 – aclweb.org … edu Abstract Computational creativity is one of the central research topics of Artificial Intel- ligence and Natural Language Process- ing today. … Irony detection appears as a difficult problem since ironic statements are used to ex- press the contrary of what is being said (Quintilien … Cited by 2 Related articles All 2 versions

Sentiment polarity detection in Spanish reviews combining supervised and unsupervised approaches MT Martín-Valdivia, E Martínez-Cámara… – Expert Systems with …, 2013 – Elsevier … Mining (OM), also known as Sentiment Analysis (SA) is a challenging task that combines data mining and Natural Language Processing (NLP … There are several issues related to OM like subjectivity detection, opinion extraction, irony detection and so on (Pang and Lee, 2008). … Cited by 16 Related articles All 5 versions

Signaling sarcasm: From hyperbole to hashtag F Kunneman, C Liebrecht, M van Mulken… – Information Processing …, 2014 – Elsevier … the same time a serious conceptual and technical challenge. In this article we introduce a sarcasm detection system for tweets, messages on the microblogging service offered by Twitter. 1 In doing this we are helped by the …

Care more about customers: Unsupervised domain-independent aspect detection for sentiment analysis of customer reviews A Bagheri, M Saraee, F De Jong – Knowledge-Based Systems, 2013 – Elsevier … For the past few years, sentiment analysis (or opinion mining) for online customer reviews has attracted a great deal of attentions from researchers of data mining and natural language processing [1], [3], [5], [7], [8], [11], [9], [24], [25], [27] and [33]. … Cited by 3 Related articles All 7 versions

Survey on Product Review Sentiment Classification and Analysis Challenges M Himmat, N Salim – Proceedings of the First International Conference on …, 2014 – Springer … irony) is a sophisticated form of speech act in which the speakers provide enhancement of the semi-supervised sarcasm identification algorithm (SASI … This type of opinion is very difficult to be explored by using the available natural language processing tools be- cause there is … Related articles

Human Judgment on Humor Expressions in a Community-Based Question-Answering Service. M Inoue – AAAI Fall Symposium: Artificial Intelligence of Humor, 2012 – aaai.org … humor recognition to irony detection: The figurative language of social media. Data and Knowledge Engineering 74:1–12. Snow, R.; O’Connor, B.; Jurafsky, D.; and Ng, AY 2008. Cheap and fast—but is it good?: evaluating non-expert an- notations for natural language tasks. … Related articles All 5 versions

The Challenge of Processing Opinions Expressed in Online Contents in the Social Web Era – Language Engineering for Online Reputation …, 2012 – lrec-conf.org … toward the subject.” Yi et al.(2003), in their paper “Sentiment Analyzer: Extracting sentiments about a given topic using natural language processing techniques … Even if some work has been done in this sense, the issues of sarcasm/irony detection and of bias detection are still far … Related articles All 2 versions

Mocking Ads Through Mobile Web Services L Gatti, M Guerini, O Stock… – Computational …, 2014 – Wiley Online Library … Creative natural language processing (Veale, 2012) is an emerging topic that aims to foster linguistic creativity in humans through computational means … As for recognition, an initial work on irony detection is presented in Reyes, Rosso, and Veale (2013), despite the fact that it is …

Formalization and Rules for Recognition of Satirical Irony L Kong, L Qiu – Asian Language Processing (IALP), 2011 International …, 2011 – cs.cmu.edu Page 1. Formalization and Rules for Recognition of Satirical Irony Lingpeng Kong Department of Computer Science and Technology Beijing Language and Culture University Beijing, China e-mail: ikekonglp@gmail.com Likun … Cited by 1 Related articles All 5 versions

The perfect solution for detecting sarcasm in tweets #not CC Liebrecht, FA Kunneman, APJ van den Bosch – 2013 – repository.ubn.ru.nl … Learning the scope of negation in biomedical texts. In Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing, pages 715– 724. DC Muecke. … 2012a. From hu- mor recognition to irony detection: The figurative lan- guage of social media. … Cited by 17 Related articles All 9 versions

Sentiment analysis in Facebook and its application to e-learning A Ortigosa, JM Martín, RM Carro – Computers in Human Behavior, 2014 – Elsevier … Recent work in natural language processing focuses on the detection of these figures, such as (Reyes, Rosso, & Buscaldi, 2012), that build a training dataset of messages written in Twitter with the hashtag ‘#irony’ in order to set a model with machine-learning techniques. … Cited by 8 Related articles All 3 versions

Using explicit linguistic expressions of preference in social media to predict voting behavior S O’Banion, L Birnbaum – Advances in Social Networks …, 2013 – ieeexplore.ieee.org … For each topic or domain, the task becomes how to implement a natural language pro- cessing technique to accurately identify the expression, and … Sarcasm detection in Twitter (and in general) has proven to be a difficult task [6], and admittedly these techniques are not perfect. … Cited by 1 Related articles All 2 versions

The Linguistics of Sentiment Analysis L Hart – 2013 – pdxscholar.library.pdx.edu … For the sake of space, this paper will deal only with Natural Language Processing and Sentiment … These include algorithms, machine learning, natural language processing, linguistic features, and methods for measuring the success of a sentiment analysis system. … Related articles

Multi-Lingual Sentiment Analysis of Social Data Based on Emotion-Bearing Patterns C Argueta, YS Chen – SocialNLP 2014, 2014 – aclweb.org Proceedings of the Second Workshop on Natural Language Processing for Social Media (SocialNLP), pages 38–43, Dublin, Ireland, August 24 2014 … emotion-bearing patterns can be used to perform a more complex analysis such as ambiguity and sarcasm identification, and to …

Crowd explicit sentiment analysis A Montejo-Ráez, MC Díaz-Galiano… – Knowledge-Based …, 2014 – Elsevier … 2. Sentiment analysis in social media. Sentiment Analysis (also known as Opinion Mining) is one of the most active research areas in Natural Language Processing nowadays [28], with special interest in the classification of texts into positive, negative or neutral. … Related articles

“Our Grief is Unspeakable”: Automatically Measuring the Community Impact of a Tragedy K Glasgow, C Fink, J Boyd-Graber – 2014 – aaai.org … The LIWC death category concerns death and dying. Its dictionary contains twenty-nine stems of content words in- cluding dead, burial, and coffin. The application of any dic- tionary to natural language will of course have limitations. … Related articles All 2 versions

Applications in Intelligent Speech Analysis B Schuller – Intelligent Audio Analysis, 2013 – Springer … In: HLT ’05: Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing, pp. … NeuroImage 47(4), 2005–2015 (2009) CrossRef; Tepperman, J., Traum, D., Narayanan, S.: “Yeah Right”: sarcasm recognition for spoken … Related articles

Measuring the quality of hybrid opinion mining model for e-commerce application G Vinodhini, RM Chandrasekaran – Measurement, 2014 – Elsevier With the rapid expansion of e-commerce over the decades, the growth of the user generated content in the form of reviews is enormous on the Web. A need to organ. Cited by 1 Related articles

Research Challenge on Opinion Mining and Sentiment Analysis D Osimo, F Mureddu – Universite de Paris-Sud, Laboratoire LIMSI-CNRS, …, 2012 – w3.org … Visual representation · Audiovisual opinion mining · Real-time opinion mining · Machine learning algorithms · Natural language interfaces · SNA … mining · Usable, peer- to-peer opinion mining tools for citizens · Non-bipolar assessment of opinion · Automatic irony detection Cited by 5 Related articles All 2 versions

Combining supervised and unsupervised polarity classification for non-english reviews JM Perea-Ortega, E Martínez-Cámara… – … and Intelligent Text …, 2013 – Springer … Opinion Mining (OM), also known as Sentiment Analysis (SA) is a challenging task that combines data mining and Natural Language Processing (NLP) tech- niques … There are several issues re- lated to OM like subjectivity detection, opinion extraction, irony detection and so on. … Related articles All 2 versions

Exploring the importance of modification relation for emotional keywords annotation and emotion types recognition Y Wu, K Kita, F Ren, K Matsumoto… – International Journal of …, 2011 – inass.sakura.ne.jp … sification using Machine Learning”, Proceedings of the Conference on Conference on Empirical Methods in Natural Language Processing, July … Reyes and Paolo Rosso,“Mining Subjective Knowledge from Customer Reviews:A Specific Case of Irony Detection”, Proceedings of … Cited by 2 Related articles All 3 versions

Uncovering source code reuse in large?scale academic environments E Flores, A Barrón?Cedeño, L Moreno… – Computer Applications …, 2014 – Wiley Online Library … In Coursera, online lectures are crowd-taught. In its Computer Science courses, programming homework is assigned to thousands of students around the globe (eg the 2012 lecture on Natural Language Processing was reported to have over 50K enrolled students). …

General semantics K Allan – Pragmatics in Practice, 2011 – books.google.com … as environment. (Korzybski 1958 [1933]: xxx) General semantics is unlike other schools of semantics because it makes no pretence of proposing a theory, or even systematic study, of meaning in natural language. The reason … Cited by 1 Related articles All 4 versions

Computational humour C Strapparava, O Stock, R Mihalcea – Emotion-oriented systems, 2011 – Springer … Abstract. Computational humour is a challenge with connections and implications in many artificial intelligence areas, including natural language processing, intelligent human–computer interaction, and reasoning, as well as in other fields such as cognitive science, linguistics … Cited by 8 Related articles All 3 versions

Opinion mining and sentiment analysis on a Twitter data stream B Gokulakrishnan, P Priyanthan… – Advances in ICT for …, 2012 – ieeexplore.ieee.org … Further, slang usage and sentences with dubious grammar increase the requirement for preprocessing exponentially. Due to such limitations irl natural language processing, this issue becomes a bottleneck in irlcreasing the accuracy of the results. … Related articles

‘How was your day?’ SG Pulman, J Boye, M Cavazza, C Smith… – Proceedings of the …, 2010 – dl.acm.org … effect. 6 Natural Language Understanding and Dialogue Management … CA. J Tepperman, D Traum, and S Narayanan, 2006, ‘Yeah right’: Sarcasm recognition for spoken dialogue systems, In- terspeech 2006, Pittsburgh, PA, 2006. … Cited by 8 Related articles All 8 versions

Irony Detection On Turkish Microblog Texts H TA?LIO?LU – 2014 – etd.lib.metu.edu.tr … Due to the morphological structure of Turkish, various methods are applied to increase the success and quality of classification. Page 6. vi Keywords: Irony Detection, Turkish, Natural Language Processing, Microblogs, Sentiment Analysis Page 7. vii ÖZ …

[BOOK] State-of-the-Art of Social Media Analytics Research ZN Gastelum, KM Whattam – 2013 – pnnl.gov … are developing capabilities to estimate geographic regions from unstructured, non-geo-referenced text based on natural language processing, geo … x Reyes, Antonio, Paulo Rosso, and Davide Buscaldi (2012), “From humor recognition to irony detection: The figurative language … All 2 versions

The socialist network M Van De Camp, A Van Den Bosch – Decision Support Systems, 2012 – Elsevier We develop and test machine learning-based tools for the classification of personal relationships in biographical texts, and the induction of social networks fr. Cited by 3 Related articles All 9 versions

Recognizing Humor on Twitter R Zhang, N Liu – Proceedings of the 23rd ACM International Conference …, 2014 – dl.acm.org … We believe our novel findings will inform and inspire the burgeoning field of computational humor research in the social media. Categories and Subject Descriptors I.2.7 [Artificial Intelligence]: Natural Language Processing –Text analysis. …

Classifying with Co-stems N Lipka, B Stein – Advances in Information Retrieval, 2011 – Springer … [8] Language Identification Determine the language of d. [3] Sarcasm Detection Determine whether d is sarcastic. [20] … In: Proc. of the Conference on Empirical Methods in Natural Language Processing, pp. 79–86 (2002) 14. Porter, MF: An algorithm for suffix stripping. … Cited by 1 Related articles All 8 versions

Compositionality and sandbag semantics EG Unnsteinsson – Synthese, 2014 – Springer … Seeing that natural language contains a potential infinity of compound expressions (because of recursion), it is impossible that people learn their meanings directly one by one—there must be some computational process involved. … Related articles All 2 versions

Extraction of High-Level Semantically Rich Features from Natural Language Text D Bogdanova – ADBIS (2), 2011 – ceur-ws.org … This thesis aims at extracting high-level semantically rich features from natural language text … Furthermore, this area will benefit from irony detection, because ironical utterances of a word have the opposite polarity from literal meaning, eg positive adjective good is negative while … Cited by 1 Related articles All 2 versions

TASS 2013-A second step in reputation analysis in Spanish J Villena Román, J García Morera, S Lana Serrano… – 2014 – rua.ua.es … Sentiment analysis is the application of natural language processing and text analytics to identify and extract subjective information from texts. … issues, the development of new corpus with different varieties of Spanish, and some tasks related to irony detection, mixed sentiments … Cited by 3 Related articles All 5 versions

“I Wanted to Predict Elections with Twitter and all I got was this Lousy Paper”–A Balanced Survey on Election Prediction using Twitter Data D Gayo-Avello – arXiv preprint arXiv:1204.6441, 2012 – arxiv.org … Accurate sentiment analysis of political tweets. Please note that humor and sarcasm detection would play a major role here. … Asian Federation of Natural Language Processing. [3] Johan Bollen, Huina Mao, and Xiao-Jun Zeng. Twitter mood predicts the stock market. J. Comput. … Cited by 31 Related articles All 9 versions

Applications of opinion mining to data journalism J Ottaviani – 2013 – sapientia.ualg.pt … Jacopo Ottaviani Dissertation for obtaining the Master Degree in International Masters in Human Language Technology and Natural Language Processing 15th of April 2013 … world. Natural language processing and, in particular, sentiment analysis are key … Related articles All 2 versions

Two Thumbs Up! Sentiment Analysis in Film Reviews DJA van Kollenburg – 2014 – dspace.library.uu.nl … might in some cases be marked separately. Another task in Natural Language Processing that is applicable to the field of sentiment mining is that of Named Entity Recognition. If the … they would certainly not be useful in sarcasm detection. New data were tested on the basis of …

The role of sentiment in the social web M Thelwalla, A Kappasb – Collective Emotions, 2014 – books.google.com … Psychological aspects of natural language use: Our words, our selves. Annual Review ofPsychology, 54, 547–577. Reyes, A., & Rosso, P.(2011). Mining subjective knowledge from customer reviews: A specific case of irony detection. … Cited by 1 Related articles All 2 versions

Graduation Project Bachelor Computer Science Thesis F Kroon – 2013 – science.uva.nl … One of the aspects of natural language that is very common in daily language but at least as hard to detect by a computer is irony, or sarcasm if used to taunt someone (often used interchangeably). … [10] to check a human baseline in sarcasm detection against their own research. … Related articles

Towards the Development of Learning Analytics: Student Speech as an Automatic and Natural Form of Assessment M Worsley, P Blikstein – Annual Meeting of the American Education …, 2010 – tltl.stanford.edu … Nonetheless, recent work in smile, laughter and sarcasm detection may prove to be useful in advancing the extraction of student … Linguistic Feature Extraction Linguistic features were mined from the transcribed audio using the Python Natural Language Toolkit (NLTK) module … Cited by 6 Related articles All 3 versions

Crowdsourcing and its application J Mitrovi? – Infoteka, 2013 – infoteka.unilib.rs … Keywords crowdsourcing, microtasks, MTurk, Natural Language Processing, WordNet … Two quality control procedures were used in the project focusing on generation and analysis of a specialized corpus meant to be used for sarcasm and irony identification in texts (Filatova … Related articles All 3 versions

Humor as circuits in semantic networks I Labutov, H Lipson – Proceedings of the 50th Annual Meeting of the …, 2012 – dl.acm.org … While humor/sarcasm recognition merits direct ap- plication to the areas such as information retrieval (Friedland and Allan, 2008), sentiment classifica- tion … (3) Ranked scripts are converted to surface form by aligning a subset of its concepts to natural language templates of the … Cited by 5 Related articles All 5 versions

Sentiment analysis algorithms and applications: A survey W Medhat, A Hassan, H Korashy – Ain Shams Engineering Journal, 2014 – Elsevier … They worked on movie reviews and used Maximum Entropy (ME) classifier (illustrated with details in the next section). 3.2. Challenging tasks in FS. A very challenging task in extracting features is irony detection. The objective of this task is to identify irony reviews. … Related articles

Linguistic-based patterns for figurative language processing: the case of humor recognition and irony detection A Reyes Pérez – 2012 – riunet.upv.es Linguistic-based Patterns for Figurative Language Processing: The Case of Humor Recognition and Irony Detection Antonio Reyes Pérez … Figurative language represents one of the most difficult tasks regard- ing natural language processing. Unlike literal language, figurative … Related articles All 4 versions

A methodological framework to understand and leverage the impact of content on social media influence L Bruni – 2014 – politesi.polimi.it … More specifically, in Section 2.2.3 the state of the art re- lated to the irony detection problem is reviewed. … A further goal of this kind of analysis is that to reduce the error due to the interpretation of natural language such as irony or word sense disambiguation. … Related articles All 2 versions

Sentiment Analysis For Hindi Language P Arora – 2013 – web2py.iiit.ac.in … a writer from a given piece of text.“Sentiment analysis or opinion mining refers to the application of natural language processing, computational … Sarcasm Detection- “ Sarcasm ” is defined as a sharp, bitter, or cutting expression or remark; a bitter jibe or taunt usually conveyed … Cited by 3 Related articles

Predicting associated statutes for legal problems YH Liu, YL Chen, WL Ho – Information Processing & Management, 2014 – Elsevier … for further processing. It uses techniques from information retrieval, information extraction (IR), as well as natural language processing (NLP), and connects them using data mining, machine learning, and statistics. In general …

An Evaluative Review of the Pragmatics of Verbal Irony J Vance – 2013 – etheses.whiterose.ac.uk … Winner et al. (1998) report that right-hemisphere damage impacts irony recognition in cases where subjects are required to identify states of mutual knowledge between characters, a further indication of the link between irony recognition and ‘theory of mind’ modules. … Related articles All 2 versions

A meta-analysis of state-of-the-art electoral prediction from Twitter data D Gayo-Avello – Social Science Computer Review, 2013 – ssc.sagepub.com Page 1. Article A Meta-Analysis of State-of-the- Art Electoral Prediction From Twitter Data Daniel Gayo-Avello1 Abstract Electoral prediction from Twitter data is an appealing research topic. It seems relatively straightfor- ward and the prevailing view is overly optimistic. … Cited by 20 Related articles All 11 versions

Fine-Grained Opinion Mining from Different Genre of Social Media Content A Bakliwal – 2013 – web2py.iiit.ac.in … Sentiment Analysis is a combination of natural language processing, computational linguistics and information extraction and is applied to extract subjective information from text. Every textual information can be categorized into two main classes: Opinions and Facts. … Related articles

Understanding preferences and similarities from user-authored text: applications to search and recommendations G Ganu – 2014 – rucore.libraries.rutgers.edu … The staff ignored my friends and I the entire time we were there…You guys are awesome!” Sarcasm detection is a notably hard task [49]. Our techniques in Chapter 3 assess reviews at the sentence level, thus breaking down the effect of assigning oppositely polar sentiments to … Related articles

[BOOK] Interpreting figurative meaning RW Gibbs Jr, HL Colston – 2012 – books.google.com Page 1. interpreting figurative meaning Interpreting Figurative Meaningcritically evaluates the recent empirical work from psycholinguistics and neuroscience examining the successes and diffi- culties associated with interpreting figurative language. … Cited by 34 Related articles All 3 versions

Intelligent Information Processing Chances of Crowdsourcing WT Balke – 2013 – nii.ac.jp … ontology cleaning, or data cleaning • Sensor data stream processing (eg, energy efficient stream join, uncertain stream processing) • Obtaining cognitive meta-data from natural-language, as for example sen- timent or emotion analysis, intention detection, sarcasm detection, etc … Related articles

International Research Roadmap on ICT Tools for Governance and Policy Modelling Interim Version D Osimo, F Mureddu, R Onori, S Armenia – 2012 – crossover-project.eu Page 1. 0204F01_International Research Roadmap on ICT tools for Governance and Policy Modelling ICT Seventh Framework Programme (ICT FP7) Grant Agreement No: 288828 Bridging Communities for Next Generation Policy-Making … Related articles All 4 versions

Using Social Media Content to Inform Agent-based Models for Humanitarian Crisis Response S Wise – 2014 – digilib.gmu.edu Page 1. USING SOCIAL MEDIA CONTENT TO INFORM AGENT-BASED MODELS FOR HUMANITARIAN CRISIS RESPONSE by Sarah Wise A Dissertation Submitted to the Graduate Faculty of George Mason University In Partial …

Irony in online reviews: A linguistic approach to identifying irony M Jönsson – 2010 – gupea.ub.gu.se … I will carry out this investigation manually, but the goal is that my findings could be used in NLP (natural language processing) applications … to identify the semantic orientation of words in order to extract antonyms, but their ap- proach is interesting for irony identification as well … Cited by 1 Related articles All 3 versions

Perceptual Shape Analysis: approaching geometric problems with elements of perception psychology F Guggeri – 2012 – veprints.unica.it Page 1. i i “phdthesis” — 2012/2/26 — 19:44 — page 1 — #1 i i i i i i University of Cagliari PhD School of Mathematics and Scientific Computing Perceptual Shape Analysis Approaching geometric problems with elements of perception psychology Author: Fabio Guggeri … Related articles

Exploring Crowdsourcing to Personalize Web Experiences D Aggarwal – 2013 – web2py.iiit.ac.in Page 1. Exploring Crowdsourcing to Personalize Web Experiences Thesis submitted in partial fulfillment of the requirements for the degree of MS by research in Computer Science & Engineering by Deepti Aggarwal 201007001 deepti.aggarwal@research.iiit.ac.in … Related articles