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A Generate-and-Test Method of Detecting Negative-Sentiment Sentences [chapter]

Yoonjung Choi, Hyo-Jung Oh, Sung-Hyon Myaeng
2012 Lecture Notes in Computer Science  
The proposed method is geared toward detecting negative sentiment sentences as they are not appropriate for suggesting contextual ads.  ...  The main strategy is to learn and weight sentiment-revealing clues by first generating a maximal set of candidates from the annotated sentences for maximum recall and learning a classifier using linguistically-motivated  ...  The Generate-and-Test Approach The overall strategy is to follow the "generate and test paradigm": we first generate a maximal set of negative clue candidates to identify potentially negative sentences  ... 
doi:10.1007/978-3-642-28604-9_41 fatcat:ottam5eiuncypnenym2gwfarcm

Sentiment-Aspect Analysis through Semi-Supervised Topic Modeling

Yong Heng Chen, Wanli Zuo, Hao Yue, Yaojin Lin
2015 International Journal of Database Theory and Application  
Although a great many of approaches have been proposed in detecting aspects and the relevant aspect-specific sentiments, most of them detect the latent aspects with no proper classifying them or classify  ...  Sentiment analysis based on the aspects of products or services is designed to explore subjective information such as attitudes and opinions in user-generated reviews.  ...  Thus, possible future directions for this work include test our method on other dataset and achieve online fashion to perform detection and analysis of aspects.  ... 
doi:10.14257/ijdta.2015.8.6.16 fatcat:755qlhbsmfhoporuu63lggppci

COMMIT-P1WP3: A Co-occurrence Based Approach to Aspect-Level Sentiment Analysis

Kim Schouten, Flavius Frasincar, Franciska de Jong
2014 Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014)  
We present a simple aspect detection algorithm, a co-occurrence based method for category detection and a dictionary based sentiment classification algorithm.  ...  The failure analysis and related work section focus mainly on the category detection method as it is most distinctive for our work.  ...  Both data sets are split into a training set of roughly 3000 sentences and a test set of 800 sentences.  ... 
doi:10.3115/v1/s14-2032 dblp:conf/semeval/SchoutenFJ14 fatcat:m62dizcmmffa7elyyeqzuhgcwy

An Evaluation Framework and Adaptive Architecture for Automated Sentiment Detection [chapter]

Stefan Gindl, Johannes Liegl, Arno Scharl, Albert Weichselbraun
2009 Studies in Computational Intelligence  
This work provides an overview of different dictionary-and machine-learning-based sentiment detection methods and evaluates them on several Web corpora.  ...  Small corpus size, ambiguity and subtle incremental change of tonal expressions between different versions of a document complicate sentiment detection.  ...  Acknowledgment This work was developed as a part of the RAVEN (Relation Analysis and Visualization for Evolving Networks; research project funded by the Austrian Ministry of  ... 
doi:10.1007/978-3-642-02184-8_15 fatcat:wyxklhwcbnf7zpn6hhs7voawd4

A C4.5 algorithm for english emotional classification

Phu Vo Ngoc, Chau Vo Thi Ngoc, Tran Vo Thi Ngoc, Dat Nguyen Duy
2017 Evolving Systems  
negative polarity are created by the decision tree. Classifying sentiments of one English document is identified based on the association rules of the positive polarity and the negative polarity.  ...  We have tested our new model on our testing data set and we have achieved 60.3% accuracy of sentiment classification on this English testing data set.  ...  Li and Liu 2014; Turney 2002; Lee et al. 2002; Zyl 2002; Le Hegarat-Mascle et al. 2002; Ferro-Famil and Pottier 2002; Chaovalit and Zhou 2005; Lee and Lewicki 2002; Gllavata et al. 2004) , to understand  ... 
doi:10.1007/s12530-017-9180-1 fatcat:ks3xxs5v4neypl7aeibnnzzrru

TJUdeM: A Combination Classifier for Aspect Category Detection and Sentiment Polarity Classification

Zhifei Zhang, Jian-Yun Nie, Hongling Wang
2015 Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)  
This paper describes the system we submitted to In-domain ABSA subtask of SemEval 2015 shared task on aspect-based sentiment analysis that includes aspect category detection and sentiment polarity classification  ...  For the sentiment polarity classification, we combined an SVM classifier with a lexicon-based polarity classifier.  ...  Acknowledgments We are really grateful to the organizers and reviewers for this interesting task and their helpful suggestions and comments.  ... 
doi:10.18653/v1/s15-2131 dblp:conf/semeval/ZhangNW15 fatcat:oejma4mvzrhwnmjlzorrkjc5uu

Aspect Based Sentiment analysis SemEval-2014 Task 4

2014 Asian Journal of Computer Science And Information Technology  
The "Aspect Based Sentiment Analysis" task focuses on the recognition of aspect term and category and classification of emotions (positive, negative, conflict, neutral) in restaurant reviews for the aspect  ...  In this paper we propose the system for recognizing aspects and analyzing the sentiments using SVM for the restaurant review dataset.  ...  ACKNOWLEDGMENT The authors would like to welcome the reviewers for their critical and constructive comments and suggestions. The authors would like to thank the Authorities of Dr.  ... 
doi:10.15520/ajcsit.v4i8.9 fatcat:5tuu7sk6mjberhaut3xcupc2h4

Analysis of Emoticon and Sarcasm Effect on Sentiment Analysis of Indonesian Language on Twitter

Debby Alita, Sigit Priyanta, Nur Rokhman
2019 Journal of Information Systems Engineering and Business Intelligence  
the same testing data using classification method are Naïve Bayes Classifier and Support Vector Machine.  ...  The detection of superior sarcasm only by using the Naïve Bayes Classifier method due to differences in the amount of sarcasm data and not sarcasm in the research process.Keywords: Emoticon, Naïve Bayes  ...  RESULTS A. Results of testing sentiment analysis In the sentiment analysis test without sarcasm detection using 2 methods namely Naïve Bayes Classifier and Support Vector Machine.  ... 
doi:10.20473/jisebi.5.2.100-109 fatcat:4mt4mgoo4zbibgqwea5bjw4tpy

Sentiment Analysis of Citations Using Word2vec [article]

Haixia Liu
2017 arXiv   pre-print
Using 10-cross-validation scheme, evaluation was conducted on a set of annotated citations. The results showed that word embeddings are effective on classifying positive and negative citations.  ...  I also investigated polarity-specific word embeddings (PS-Embeddings) for classifying positive and negative citations.  ...  this method was not as good as hand-crafted features, such as n-grams and sentence structure features.  ... 
arXiv:1704.00177v1 fatcat:nvogofdstnan3ehs2ouubijhx4

A query-specific opinion summarization system

Feng Jin, Minlie Huang, Xiaoyan Zhu
2009 2009 8th IEEE International Conference on Cognitive Informatics  
The system has several modules to be able to do this: a question analysis and query reformulation module, a latent semantic indexing based sentence scoring module, a sentence polarity detection module,  ...  and a redundancy removal module.  ...  A large number of methods and tools have been developed for opinion detection, search, mining and summarization, etc.  ... 
doi:10.1109/coginf.2009.5250700 dblp:conf/IEEEicci/JinHZ09 fatcat:aow7os5u6rawvbvwyr52xogpv4

Potential and Limitations of Commercial Sentiment Detection Tools

Mark Cieliebak, Oliver Dürr, Fatih Uzdilli
2013 International Conference of the Italian Association for Artificial Intelligence  
In this paper, we analyze the quality of several commercial tools for sentiment detection. All tools are tested on nearly 30,000 short texts from various sources, such as tweets, news, reviews etc.  ...  In addition to the quality analysis (measured by various metrics), we also investigate the effect of increasing text length on the performance.  ...  Acknowledgments We would like to thank all tool providers for giving us the opportunity to test and evaluate their systems for free, and for their excellent support.  ... 
dblp:conf/aiia/CieliebakDU13 fatcat:xwulf4va4rfkpgynfkjzjmwbaa

NEUOM: Identifying Opinionated Sentences in Chinese and English Text

Chunliang Zhang, Ke Wang, Muhua Zhu, Tong Xiao, Jingbo Zhu
2008 NTCIR Conference on Evaluation of Information Access Technologies  
NEUOM system adopts a sentiment lexicon-based(SLB) approach to identifying opinionated sentences in a Chinese text and English text.  ...  This paper introduces our NEUOM system which participates in the opinionated sentence detection task, one of evaluation tasks in Multilingual Opinion Analysis Task (MOAT) of NTCIR-7.  ...  Therefore, the second critical problem of a dictionary-based method is how to determine the appropriate polarity of a sentiment word in the opinionated sentence detection tasks, for a sentiment word of  ... 
dblp:conf/ntcir/ZhangWZXZ08 fatcat:4exgzquckfbc7fe5p5drcif3zu

Semi-supervised Aspect Based Sentiment Analysis for Movies Using Review Filtering

Deepa Anand, Deepan Naorem
2016 Procedia Computer Science  
The aspect and sentiment detection using all the three schemes is empirically evaluated against a manually constructed test set.  ...  Secondly we propose a scheme to detect aspects and the corresponding opinions using a set of hand crafted rules and aspect clue words.  ...  Detection Accuracy of M, KC and KRC methods; (b) Aspect-Sentiment Detection Accuracy of M, KC and KRC methods. 5.  ... 
doi:10.1016/j.procs.2016.04.070 fatcat:qijijlam4zclhev6zjpwosicc4

CLINE: Contrastive Learning with Semantic Negative Examples for Natural Language Understanding [article]

Dong Wang, Ning Ding, Piji Li, Hai-Tao Zheng
2021 arXiv   pre-print
Empirical results show that our approach yields substantial improvements on a range of sentiment analysis, reasoning, and reading comprehension tasks.  ...  To study the impact of semantics caused by small perturbations, we conduct a series of pilot experiments and surprisingly find that adversarial training is useless or even harmful for the model to detect  ...  and the task is to predict the sentiment (positive or negative) of a movie review.  ... 
arXiv:2107.00440v1 fatcat:6q4tik5o5vg2xhphvcky5gg3ka

Topic Detection and Summarization of User Reviews [article]

Pengyuan Li, Lei Huang, Guang-jie Ren
2020 arXiv   pre-print
Sentiment analysis is employed to distinguish positive and negative opinions among each detected topic.  ...  To test our method, a new dataset comprising product reviews and summaries about 1028 products are collected from Amazon and CNET.  ...  Thus, given a review sentence s j i , we can obtain a positive sentiment score, P S j i , and a negative sentiment score, neg P S j i by using VADER.  ... 
arXiv:2006.00148v1 fatcat:ynanvueqgbhtffiplpkz2hpltq
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