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Entity-centric topic-oriented opinion summarization in twitter
2012
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '12
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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
2016
International Journal of Research in Engineering and Technology
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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
2017
International Journal of Advanced Research in Computer Science
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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
2018
International Journal of Intelligent Engineering and Systems
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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
2017
Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (*SEM 2017)
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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]
2018
arXiv
pre-print
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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
2016
Proceedings of the 25th International Conference Companion on World Wide Web - WWW '16 Companion
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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
2020
Zenodo
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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
2018
ACM Transactions on Management Information Systems
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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
2019
International Journal of Scientific Research in Computer Science Engineering and Information Technology
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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
2013
Journal of Information Processing Systems
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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]
2017
arXiv
pre-print
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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
2019
International Journal of Research in Advent Technology
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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
2015
International Journal of Computer Applications
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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
2017
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers
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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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