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32
Tracking Sentiment Analysis through Twitter
"... Abstract – Social media continues to gain increased presence and importance in society. Public and private opinions about a wide variety of subjects are expressed and spread continually via numerous social media, with Twitter being among the most timely. The ability to quantify and evaluate society’ ..."
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and its implementation in the form of a webbased application that can quantify sentiment contained in Twitter feeds and track the sentiment as it changes over time. Results are provided that evaluate the tool for use in performing tracking of sentiment analysis as perceptions change over time. post
WarwickDCS: From Phrase-Based to Target-Specific Sentiment Recognition
"... We present and evaluate several hybrid sys-tems for sentiment identification for Twit-ter, both at the phrase and document (tweet) level. Our approach has been to use a novel combination of lexica, traditional NLP and deep learning features. We also analyse tech-niques based on syntactic parsing and ..."
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and token-based association to handle topic specific sen-timent in subtask C. Our strategy has been to identify subphrases relevant to the designated topic/target and assign sentiment according to our subtask A classifier. Our submitted subtask A classifier ranked fourth in the Se-mEval official results
Semi-Supervised Recognition of Sarcastic Sentences in Twitter and Amazon
"... Sarcasm is a form of speech act in which the speakers convey their message in an implicit way. The inherently ambiguous nature of sarcasm sometimes makes it hard even for humans to decide whether an utterance is sarcastic or not. Recognition of sarcasm can benefit many sentiment analysis NLP applica ..."
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Sarcasm is a form of speech act in which the speakers convey their message in an implicit way. The inherently ambiguous nature of sarcasm sometimes makes it hard even for humans to decide whether an utterance is sarcastic or not. Recognition of sarcasm can benefit many sentiment analysis NLP
Sentiment Analysis on Monolingual, Multilingual and Code-Switching Twitter Corpora
"... We address the problem of performing po-larity classification on Twitter over differ-ent languages, focusing on English and Spanish, comparing three techniques: (1) a monolingual model which knows the language in which the opinion is written, (2) a monolingual model that acts based on the decision p ..."
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We address the problem of performing po-larity classification on Twitter over differ-ent languages, focusing on English and Spanish, comparing three techniques: (1) a monolingual model which knows the language in which the opinion is written, (2) a monolingual model that acts based on the decision
Be Conscientious, Express your Sentiment!
"... Abstract. This paper addresses the issue of how personality recognition can be helpful for sentiment analysis. We exploited the corpus for sentiment analysis released for the SEMEVAL 2013, we automatically annotated personality labels by means of an unsupervised system for personality recognition. W ..."
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Abstract. This paper addresses the issue of how personality recognition can be helpful for sentiment analysis. We exploited the corpus for sentiment analysis released for the SEMEVAL 2013, we automatically annotated personality labels by means of an unsupervised system for personality recognition
A Novel Reason Mining Algorithm to Analyze Public Sentiment Variations on Twitter and Facebook
"... With the explosive growth of social media on web, analyzing Public Sentiment Variations (PSV) has become utmost necessity as public sentiments fluctuate with alterations in real life events. Analysis of PSV empowers decision makers to gain a better understanding of public reactions in social, politi ..."
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, political and economic environment thus helps in better decision making. Most of the recent studies are bounded to be analyzing and predicting public sentiments. In this paper, we have done further analysis to know the useful insights for PSV using tweets and Facebook comments with a specific target. We
Data Analysis of Twitter feeds on Google Maps
"... Abstract: With increasing popularity in microblogging sites, we are in the era of information explosion. As of June 2011, about 200 million tweets are being generated every day. Spurred by that growth, companies and media organizations are increasingly seeking ways to mine Twitter for information a ..."
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and the applications of using a Twitter and Google maps mashup. Further, we analyze the sentiments expressed within a particular sentence, paragraph or document etc. The analysis based on sentiments can pave way for automatic trend analysis, topic recognition and opinion mining etc. Furthermore, we can fairly estimate
Sarcasm as contrast between a positive sentiment and negative situation.
- In Proceedings of EMNLP.
, 2013
"... Abstract A common form of sarcasm on Twitter consists of a positive sentiment contrasted with a negative situation. For example, many sarcastic tweets include a positive sentiment, such as "love" or "enjoy", followed by an expression that describes an undesirable activity or sta ..."
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Abstract A common form of sarcasm on Twitter consists of a positive sentiment contrasted with a negative situation. For example, many sarcastic tweets include a positive sentiment, such as "love" or "enjoy", followed by an expression that describes an undesirable activity
WEB FORUMS CRAWLER FOR ANALYSIS USER SENTIMENTS
"... The advancement in computing and communication technologies enables people to get together and share information in innovative ways. Social networking sites empower people of different ages and backgrounds with new forms of collaboration, communication, and collective intelligence. This project pres ..."
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and are powered by different forum software packages, they always have similar implicit navigation paths connected by specific URL types to lead users from entry pages to thread pages. Based on this observation, the web forum crawling problem is reduced to a URL-type recognition problem and classifies them
#Irony or #Sarcasm— A Quantitative and Qualitative Study Based on Twitter
"... Current study is with the aim to identify similarities and distinctions between irony and sarcasm by adopting quantitative sentiment analysis as well as qualitative content analysis. The result of quantitative sentiment analysis shows that sarcastic tweets are used with more positive tweets than iro ..."
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awareness. Thus, tweets of first sense of irony may attack a specific target, and the speaker may tag his/her tweet irony because the tweet itself is ironic. These tweets though tagged as irony are in fact sarcastic tweets. Different from this, the tweets of second sense of irony is tagged to classify
Results 1 - 10
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32