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Entity-centric topic-oriented opinion summarization in twitter

Xinfan Meng, Furu Wei, Xiaohua Liu, Ming Zhou, Sujian Li, Houfeng Wang
2012 Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '12  
Afterwards, we develop a target (i.e. entity) dependent sentiment classification approach to identifying the opinion towards a given target (i.e. entity) of tweets.  ...  Twitter generates a huge volume of instant messages (i.e. tweets) carrying users' sentiments and attitudes every minute, which both necessitates automatic opinion summarization and poses great challenges  ...  O'Connor et al. determine the sentiments by subjective Lexicon [21] . Jiang et al. study target-dependent Twitter sentiment classification [13] . Wang et al.  ... 
doi:10.1145/2339530.2339592 dblp:conf/kdd/MengWLZLW12 fatcat:arp42ptlqbcpjmd34kpi42y37e

SECURED CLASSIFICATION OF SENTIMENTS ON TOPIC ADAPTIVE DYNAMIC TWEETS

Shrivatsa D Perur .
2016 International Journal of Research in Engineering and Technology  
The work of classifying sentiments is adaptive to subject, a classifier prepared to perform on a topic will not have same effect on other. This poses a hindrance for the analysis of sentiments.  ...  There will be various topics in Twitter, which makes the task difficult for preparing a generalized classifier for all subjects.  ...  Thus, classification of sentiment of tweets on emerging and topics that cannot be predicted, topic adaption is needed.  ... 
doi:10.15623/ijret.2016.0504041 fatcat:j27hpvqo5ffl7b4entlinigq6a

A COMPARATIVE STUDY OFSENTIMENTAL ANALYSIS IN VARIOUS TECHNIQUES

S. Indhu
2017 International Journal of Advanced Research in Computer Science  
Sentiment analysis is also known as Opinion Topic Modeling (OTM) approach. OTM is used to examine and group the user created information likecomments, articles and so on.  ...  Twitter has given a huge space for analysing movie reviews, consumer brands, election events, stock market exchange, and so on. This survey paper discusses several methods used for sentiment analysis.  ...  In this way, the topic adjustment is required for sentiment classification of tweets on developing and random subjects.  ... 
doi:10.26483/ijarcs.v8i9.5212 fatcat:g64g3a5etrcpvfvsikmz26wsmq

Possibilistic Fuzzy C-means Topic Modelling for Twitter Sentiment Analysis

Mandhula Trupthi, Suresh Pabboju, Gugulotu Narsimha
2018 International Journal of Intelligent Engineering and Systems  
Social media are generating an enormous amount of sentiment data in the form of companies getting their customers' opinions on their products, political sentiment analysis and movie reviews, etc.  ...  In this scenario, twitter sentiment analysis is undertaken for classifying and identifying sentiments or opinions expressed by people in their tweets.  ...  The topic-based mixture model for twitter sentiment helps to further improve the sentiment classification accuracy.  ... 
doi:10.22266/ijies2018.0630.11 fatcat:ysrpcblm3bc4dmbxjgip7a3vcm

Predictive Linguistic Features of Schizophrenia

Efsun Sarioglu Kayi, Mona Diab, Luca Pauselli, Michael Compton, Glen Coppersmith
2017 Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (*SEM 2017)  
For writing samples dataset, syntactic features are found to be the most successful in classification whereas for the less structured Twitter dataset, a combination of features performed the best.  ...  Schizophrenia is one of the most disabling and difficult to treat of all human medical/health conditions, ranking in the top ten causes of disability worldwide.  ...  We use the MALLET tool (Mc-Callum, 2002) to train the topic model and empirically choose number of topics based on best classification performance on a validation set.  ... 
doi:10.18653/v1/s17-1028 dblp:conf/starsem/KayiDPCC17 fatcat:hnyxenvqzfedjhydl5gstbxx5e

Predictive Linguistic Features of Schizophrenia [article]

Efsun Sarioglu Kayi, Mona Diab, Luca Pauselli, Michael Compton, and Glen Coppersmith
2018 arXiv   pre-print
For writing samples dataset, syntactic features are found to be the most successful in classification whereas for the less structured Twitter dataset, a combination of features performed the best.  ...  Schizophrenia is one of the most disabling and difficult to treat of all human medical/health conditions, ranking in the top ten causes of disability worldwide.  ...  We use the MALLET tool [12] to train the topic model and empirically choose number of topics based on best classification performance on a validation set.  ... 
arXiv:1810.09377v1 fatcat:t3ddypare5cy3conhdclacuaoy

PerSentiment

Kaisong Song, Ling Chen, Wei Gao, Shi Feng, Daling Wang, Chengqi Zhang
2016 Proceedings of the 25th International Conference Companion on World Wide Web - WWW '16 Companion  
In this demonstration, we present a live system based on Twitter called PerSentiment, an individuality-dependent sentiment classification system which makes the first attempt to analyze the personalized  ...  Despite considerable progress on microblog sentiment classification, most of the existing works ignore the influence of personal distinctions of different microblog users on the sentiments they convey,  ...  [10] and Lipenkova [5] implemented non-personalized sentiment classification systems based on Weibo and Twitter services, respectively.  ... 
doi:10.1145/2872518.2890540 dblp:conf/www/SongCGFWZ16 fatcat:wy3y2ymf2jcp5hdfplwdqx5dwu

Multi-class Sentiment Analysis on Twitter

Venkatesh, Y. Nagaraju, Sheema Sultana, A. Mamthaj, R. Priyadarshini, S. Kavya
2020 Zenodo  
Sentiment analysis and opinion mining in social networks are current research topics. The state of the art works focused on the binary and ternary classifications.  ...  In this paper, we proposed model that performs the task of multi-class classification of online posts of Twitter users.  ...  The sentiment analysis and opinion extraction on Twitter present a hot topic of research.  ... 
doi:10.5281/zenodo.4130218 fatcat:johmiw3aknbnxpmbd342obskji

The State-of-the-Art in Twitter Sentiment Analysis

David Zimbra, Ahmed Abbasi, Daniel Zeng, Hsinchun Chen
2018 ACM Transactions on Management Information Systems  
To assess the state-of-the-art in Twitter sentiment analysis, we conduct a benchmark evaluation of 28 top academic and commercial systems in tweet sentiment classification across five distinctive data  ...  Despite this attention, state-of-the-art Twitter sentiment analysis approaches perform relatively poorly with reported classification accuracies often below 70%, adversely impacting applications of the  ...  ACKNOWLEDGMENTS The authors thank collaborators in the telecommunications, health, security, tech, and retail industries for their invaluable assistance and feedback on the benchmark evaluation, error  ... 
doi:10.1145/3185045 fatcat:fzpm7xhkyvd2newi2yp3gze7gm

A Survey on Analysis of Twitter Opinion Mining Using Sentiment Analysis

Vishnu VardanReddy, Mahesh Maila, Sai Sri Raghava, Yashwanth Avvaru, Sri. V. Koteswarao
2019 International Journal of Scientific Research in Computer Science Engineering and Information Technology  
Lot of work has been done on sentiment analysis of twitter data and lot needs to be done.  ...  Analysis of opinions & its classification on the basis of polarity (positive, negative, neutral) is a challenging task.  ...  https://gate.ac.uk/ 3 Red Opal 4 Opinion finder Opinion Finder is used for analysis of different Subjective sentences related to any topic & classification of sentences is done based on their  ... 
doi:10.32628/cseit1952126 fatcat:2tddsc7kzndkbpuoizgzmgo3qu

Opinion Bias Detection Based on Social Opinions for Twitter

A-Rong Kwon, Kyung-Soon Lee
2013 Journal of Information Processing Systems  
In this paper, we propose a bias detection method that is based on personal and social opinions that express contrasting views on competing topics on Twitter.  ...  We used unsupervised polarity classification is conducted for learning social opinions on targets. The tf•idf algorithm is applied to extract targets to reflect sentiments and features of tweets.  ...  When a tweet only mentions one topic, topic i , then our system conducts a polarity classification on the topic.  ... 
doi:10.3745/jips.2013.9.4.538 fatcat:xw34tphyqnce3gyo63wi7hg4gu

Studying Positive Speech on Twitter [article]

Marina Sokolova, Vera Sazonova, Kanyi Huang, Rudraneel Chakraboty, Stan Matwin
2017 arXiv   pre-print
We present results of empirical studies on positive speech on Twitter.  ...  In fully automated studies, we tested two approaches: unsupervised statistical analysis, and supervised text classification based on distributed word representation.  ...  Choice of sentiment categories depends on the goal of sentiment analysis.  ... 
arXiv:1702.08866v1 fatcat:wnlprcqqjfa6jke3fswuszgyay

Analysis Of Behavior Extraction On Social Life Issues Using Sentiment Analysis: A Review

Obaidullah, Dr. Faiyaz Ahmad
2019 International Journal of Research in Advent Technology  
Since many useful links with a various field like politics, education, health, agriculture, religious, marketing post on twitter so we fetch the data from Twitter for sentiment analysis.  ...  For the forecast the sentiment analysis we utilized information store on the social site stockpiling.  ...  Rule-based systems that perform sentiment analysis dependent on a lot of manually crafted rules.  ... 
doi:10.32622/ijrat.76201960 fatcat:auhjlvyvhvcalmznhi7umaxjte

Design of Sentiment Analysis System using Polarity Classification Technique

Rajeshwar Rao, Sanjeeva Polepaka, Md. Rafeeq
2015 International Journal of Computer Applications  
Twitter is a medium that we can use for communication. All posted tweets we can store in one location and create archive. Archive contains new and old tweets.  ...  Now we can start the analyzation on archive tweets that's we can design effective sentiment analysis system.  ...  First choose the class labels and classify each and every topic documents separately [1] [2] . This is we can call as a document level sentiment classification.  ... 
doi:10.5120/ijca2015906159 fatcat:qx4erwq2wjcy5h5wwl7nvgjbau

TDParse: Multi-target-specific sentiment recognition on Twitter

Bo Wang, Maria Liakata, Arkaitz Zubiaga, Rob Procter
2017 Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers  
Please see the 'permanent WRAP URL' above for details on accessing the published version and note that access may require a subscription.  ...  . 2 2 Related Work: Target-dependent Sentiment Classification on Twitter The 2015 Semeval challenge introduced a task on target-specific Twitter sentiment (Rosenthal et al., 2015) which most systems  ...  Evaluation metrics: We follow previous work on target-dependent Twitter sentiment classification, and report our performance in accuracy, 3-class macro-averaged (i.e. negative, neutral and positive) F  ... 
doi:10.18653/v1/e17-1046 dblp:conf/eacl/LiakataWZP17 fatcat:dydzhpayibe2bbdid7qvsnymsq
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