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Why Question Answering using Sentiment Analysis and Word Classes

Jong-Hoon Oh, Kentaro Torisawa, Chikara Hashimoto, Takuya Kawada, Stijn De Saeger, Jun'ichi Kazama, Yiou Wang
2012 Conference on Empirical Methods in Natural Language Processing  
In this paper we explore the utility of sentiment analysis and semantic word classes for improving why-question answering on a large-scale web corpus.  ...  We combine this simple idea with semantic word classes for ranking answers to why-questions and show that on a set of 850 why-questions our method gains 15.2% improvement in precision at the top-1 answer  ...  Conclusion In this paper, we have explored the utility of sentiment analysis and semantic word classes for ranking answer candidates to why-questions.  ... 
dblp:conf/emnlp/OhTHKSKW12 fatcat:5sxl5xz5njb6xbltejvhzzb7gq

An Approach for Computing Sentiment Polarity Analysis of Complex Why-type Questions on Product Review Sites

Amit Mishra, Sanjay Kumar Jain
2014 Research in Computing Science  
Sentiment analysis has been recently used in answering why type opinion questions.  ...  We use such structure to determine sentiment polarity of why type questions and conduct experiments which obtain better results as compared to baseline average scoring methods.  ...  Related Work Based on works on opinion question answering [1, 2, 4, 5, 6] , we find that question analysis, document analysis, retrieval method and answer processing are the steps in drawing answers to  ... 
doi:10.13053/rcs-84-1-6 fatcat:vpuaghx2ljf4vdrawazbnqhdqe

A Survey on Why-Type Question Answering Systems [article]

Manvi Breja, Sanjay Kumar Jain
2019 arXiv   pre-print
To the best of our knowledge, major research in Why-type questions began in early 2000's and our work on Why-type questions can help explore newer avenues for fact-finding and analysis.  ...  The paper presents a survey on Why-type Question Answering System, details the architecture, the processes involved in the system and suggests further areas of research.  ...  There are two classes of sentiment analysis features, namely word-polarity and phrase-polarity.  ... 
arXiv:1911.04879v1 fatcat:wdvngfqkqvgfvmjn67adebwtqi

Why-Question Answering using Intra- and Inter-Sentential Causal Relations

Jong-Hoon Oh, Kentaro Torisawa, Chikara Hashimoto, Motoki Sano, Stijn De Saeger, Kiyonori Ohtake
2013 Annual Meeting of the Association for Computational Linguistics  
In this paper, we explore the utility of intra-and inter-sentential causal relations between terms or clauses as evidence for answering why-questions.  ...  To the best of our knowledge, this is the first work that uses both intra-and inter-sentential causal relations for why-QA.  ...  Here, we used semantic word classes and sentiment polarities for identifying such semantic associations between a why-question and its answer as "if a disease's name appears in a question, then answers  ... 
dblp:conf/acl/OhTHSSO13 fatcat:s6y3fw7xovgx7immdaaxjqxtxm

Universal Adversarial Triggers for Attacking and Analyzing NLP [article]

Eric Wallace, Shi Feng, Nikhil Kandpal, Matt Gardner, Sameer Singh
2021 arXiv   pre-print
For example, triggers cause SNLI entailment accuracy to drop from 89.94% to 0.55%, 72% of "why" questions in SQuAD to be answered "to kill american people", and the GPT-2 language model to spew racist  ...  Adversarial examples highlight model vulnerabilities and are useful for evaluation and interpretation.  ...  Acknowledgements We thank Hal Daumé III, Sewon Min, Suchin Gururangan, Nelson Liu, Kevin Lin, Pranav Goel, Rob Logan IV, Jamie Matthews, Ana Marasović, the members of AllenNLP and UCI NLP, and the anonymous  ... 
arXiv:1908.07125v3 fatcat:hxtw7qfbgrczpkeuizw7e3giza

A large-scale sentiment analysis for Yahoo! answers

Onur Kucuktunc, B. Barla Cambazoglu, Ingmar Weber, Hakan Ferhatosmanoglu
2012 Proceedings of the fifth ACM international conference on Web search and data mining - WSDM '12  
of a large online question answering site.  ...  We then extend this basic analysis by investigating how properties of the (asker, answerer) pair affect the sentiment present in the answer.  ...  This work was partially supported by NSF grant, IIS-0546713 and by the Spanish Centre for the Development of Industrial Technology under the CENIT program, project CEN-20101037, "Social Media" (http://  ... 
doi:10.1145/2124295.2124371 dblp:conf/wsdm/KucuktuncCWF12 fatcat:r26wl5daanbgvcafodvhipqnle

Automatic Understanding of Image and Video Advertisements [article]

Zaeem Hussain, Mingda Zhang, Xiaozhong Zhang, Keren Ye, Christopher Thomas, Zuha Agha, Nathan Ong, Adriana Kovashka
2017 arXiv   pre-print
Our data contains rich annotations encompassing the topic and sentiment of the ads, questions and answers describing what actions the viewer is prompted to take and the reasoning that the ad presents to  ...  persuade the viewer ("What should I do according to this ad, and why should I do it?")  ...  Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.  ... 
arXiv:1707.03067v1 fatcat:eekhvqmj4baxnpurlt3mhbonbq

Automatic Understanding of Image and Video Advertisements

Zaeem Hussain, Mingda Zhang, Xiaozhong Zhang, Keren Ye, Christopher Thomas, Zuha Agha, Nathan Ong, Adriana Kovashka
2017 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)  
Our data contains rich annotations encompassing the topic and sentiment of the ads, questions and answers describing what actions the viewer is prompted to take and the reasoning that the ad presents to  ...  persuade the viewer ("What should I do according to this ad, and why should I do it?")  ...  Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.  ... 
doi:10.1109/cvpr.2017.123 dblp:conf/cvpr/HussainZZYTAOK17 fatcat:lpdwh7s755dnrol5hzbnwk7sfu

Analyzing Linguistic Features for Answer Re-Ranking of Why-Questions

Manvi Breja, Sanjay Kumar Jain
2022 Journal of Cases on Information Technology  
Why-type non-factoid questions are ambiguous and involve variations in their answers.  ...  There are cases where the need is to understand the meaning and context of a document rather than finding exact words involved in question.  ...  Oh et al. (2012) trained and tested answer re-ranker using TinySVM with features combining morphological and syntactic analysis, semantic word classes based on n-grams and sentiment analysis finding word  ... 
doi:10.4018/jcit.20220701.oa10 fatcat:rd2wqn3p2ndadnh4qhqqmmta2i

Why-type Question to Query Reformulation for efficient Document Retrieval

2022 International Journal of Information Retrieval Research  
Understanding the actual need of user from a question is very crucial in non-factoid why-question answering as Why-questions are complex and involve ambiguity and redundancy in their understanding.  ...  The paper analyzes different types of why-questions and proposes an algorithm for each class to determine the focus and reformulate it into a query by appending focal terms and cue phrase 'because' with  ...  The paper performs sentiment analysis of question using VADER tool. It is an efficient to predict the positivity or negativity of a text with their magnitude. 6.  ... 
doi:10.4018/ijirr.289948 fatcat:6vqkvfyw55bv5nzlzewzaxqsna

Collation of Feasible Solutions for Domain Based Problems: An Analysis of Sentiments Based on Codeathon Activity [article]

Rajeshwari K, Preetha S, Anitha C, Lakshmi Shree K, Pronoy Roy
2021 arXiv   pre-print
Individual team were supposed to prototype a solution which was further used to build one feasible solution. The feedback from students showed different sentiments associated with day long activity.  ...  Vivid emotions and expressions of students were analysed.  ...  The feedback is pre-processed to remove punctuation's, special characters and other stop words. The Syuzhet package in R language is used to perform the sentiment analysis.  ... 
arXiv:2108.10034v1 fatcat:n2bzg576hjd6pdvfx32rsd4o64

Universal Adversarial Triggers for Attacking and Analyzing NLP

Eric Wallace, Shi Feng, Nikhil Kandpal, Matt Gardner, Sameer Singh
2019 Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)  
For example, triggers cause SNLI entailment accuracy to drop from 89.94% to 0.55%, 72% of "why" questions in SQuAD to be answered "to kill american people", and the GPT-2 language model to spew racist  ...  Adversarial examples highlight model vulnerabilities and are useful for evaluation and interpretation.  ...  Acknowledgements We thank Hal Daumé III, Sewon Min, Suchin Gururangan, Nelson Liu, Kevin Lin, Pranav Goel, Rob Logan IV, Jamie Matthews, Ana Marasović, the members of AllenNLP and UCI NLP, and the anonymous  ... 
doi:10.18653/v1/d19-1221 dblp:conf/emnlp/WallaceFKGS19 fatcat:bxpudwdtkvfsheytjctsshadxy

Classifying User Messages For Managing Web Forum Data

Sumit Bhatia, Prakhar Biyani, Prasenjit Mitra
2012 International Workshop on the Web and Databases  
All the posts in a thread are not equally useful and serve a different purpose providing different types of information (some posts contain questions, some answers, etc.).  ...  We employ features based on the post's content, structure of the thread, behavior of the participating users and sentiment analysis of post's content.  ...  We achieved decent classification accuracy and per-class analysis revealed that the best performance was achieved for classes question and suggest solution.  ... 
dblp:conf/webdb/BhatiaM12 fatcat:kfy6fn2d5jb4bebwkid4drw3ga

Automatic classification of product reviews into interrogative and noninterrogative: Generating real time answer

Saqib et al.
2019 International Journal of Advanced and Applied Sciences  
If there is no aspect in an asked question, then LSI (Latent Semantic Indexing) generate answer using classified noninterrogatives.  ...  Datasets of interrogatives are analyzed as identifying Answer Seeking questions from Arabic tweets, question conveying and not conveying Information, Rhetorical Questions while here classifying the sentences  ...  While in industry, the term sentiment analysis is more commonly used, but in academia both sentiment analysis and opinion mining are frequently employed.  ... 
doi:10.21833/ijaas.2019.08.004 fatcat:onclauv7obdwlmbcovj2kgnwfa

Linguistic characteristics of eating disorder questions on Yahoo! Answers - content, style, and emotion

Jung Sun Oh, Daqing He, Wei Jeng, Eleanor Mattern, Leanne Bowler
2013 Proceedings of the American Society for Information Science and Technology  
Using term frequency analysis, Partof-Speech (POS) analysis, and sentiment analysis, we examined linguistic content, linguistic style, and emotional expressions in two broad categories of eating disorder  ...  Answers -socio-emotional questions and informational questions.  ...  In this study, we will adopt the same approach and scrutinize the use of words in our eating disorder questions, focusing on three word classes -content words (words representing themes), function words  ... 
doi:10.1002/meet.14505001068 fatcat:twmyg6vwvbfqtluiwgroxjdj6u
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