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299
Large Scale Sentiment Analysis on Twitter with Spark
"... Sentiment analysis on Twitter data has attracted much at-tention recently. One of the system’s key features, is the immediacy in communication with other users in an easy, user-friendly and fast way. Consequently, people tend to express their feelings freely, which makes Twitter an ideal source for ..."
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Sentiment analysis on Twitter data has attracted much at-tention recently. One of the system’s key features, is the immediacy in communication with other users in an easy, user-friendly and fast way. Consequently, people tend to express their feelings freely, which makes Twitter an ideal source
From Tweets to Polls : Linking Text Sentiment to Public Opinion Time Series
, 2010
"... We connect measures of public opinion measured from polls with sentiment measured from text. We analyze several surveys on consumer confidence and political opinion over the 2008 to 2009 period, and find they correlate to sentiment word frequencies in contemporaneous Twitter messages. While our resu ..."
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Cited by 297 (11 self)
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We connect measures of public opinion measured from polls with sentiment measured from text. We analyze several surveys on consumer confidence and political opinion over the 2008 to 2009 period, and find they correlate to sentiment word frequencies in contemporaneous Twitter messages. While our
Sentiment Analysis in Twitter for Macedonian
"... We present work on sentiment analysis in Twitter for Macedonian. As this is pio-neering work for this combination of lan-guage and genre, we created suitable re-sources for training and evaluating a sys-tem for sentiment analysis of Macedonian tweets. In particular, we developed a cor-pus of tweets ..."
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We present work on sentiment analysis in Twitter for Macedonian. As this is pio-neering work for this combination of lan-guage and genre, we created suitable re-sources for training and evaluating a sys-tem for sentiment analysis of Macedonian tweets. In particular, we developed a cor-pus of tweets
Modeling public mood and emotion: Twitter sentiment and socio-economic phenomena
- IN: ICWSM
, 2011
"... We perform a sentiment analysis of all tweets published on the microblogging platform Twitter in the second half of 2008. We use a psychometric instrument to ex-tract six mood states (tension, depression, anger, vigor, fatigue, confusion) from the aggregated Twitter con-tent and compute a six-dimens ..."
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Cited by 131 (6 self)
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We perform a sentiment analysis of all tweets published on the microblogging platform Twitter in the second half of 2008. We use a psychometric instrument to ex-tract six mood states (tension, depression, anger, vigor, fatigue, confusion) from the aggregated Twitter con-tent and compute a six
Spark: Cluster Computing with Working Sets
"... MapReduce and its variants have been highly successful in implementing large-scale data-intensive applications on commodity clusters. However, most of these systems are built around an acyclic data flow model that is not suitable for other popular applications. This paper focuses on one such class o ..."
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Cited by 213 (9 self)
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MapReduce and its variants have been highly successful in implementing large-scale data-intensive applications on commodity clusters. However, most of these systems are built around an acyclic data flow model that is not suitable for other popular applications. This paper focuses on one such class
for Twitter Sentiment Analysis
"... With the booming of microblogs on the Web, people have begun to express their opinions on a wide variety of topics on Twitter and other similar services. Sentiment analysis on entities (e.g., products, organizations, people, etc.) in tweets (posts on Twitter) thus becomes a rapid and effective way o ..."
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of gauging public opinion for business marketing or social studies. However, Twitter's unique characteristics give rise to new problems for current sentiment analysis methods, which originally focused on large opinionated corpora such as product reviews. In this paper, we propose a new entity
S.: Large-scale sentiment analysis for news and blogs
- In: Proc. Int. Conf. Weblogs and Social Media (ICWSM
, 2007
"... News can be good or bad, but it is seldom neutral. Although full comprehension of natural language text remains well be-yond the power of machines, the statistical analysis of rela-tively simple sentiment cues can provide a surprisingly mean- ..."
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Cited by 98 (13 self)
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News can be good or bad, but it is seldom neutral. Although full comprehension of natural language text remains well be-yond the power of machines, the statistical analysis of rela-tively simple sentiment cues can provide a surprisingly mean-
Learning sentiment-specific word embedding for twitter sentiment classification.
- In ACL,
, 2014
"... Abstract We present a method that learns word embedding for Twitter sentiment classification in this paper. Most existing algorithms for learning continuous word representations typically only model the syntactic context of words but ignore the sentiment of text. This is problematic for sentiment a ..."
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Cited by 25 (1 self)
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. Specifically, we develop three neural networks to effectively incorporate the supervision from sentiment polarity of text (e.g. sentences or tweets) in their loss functions. To obtain large scale training corpora, we learn the sentiment-specific word embedding from massive distant-supervised tweets collected
Want to be retweeted? Large scale analytics on factors impacting retweet in Twitter network
- in Proceedings of the IEEE Second International Conference on Social Computing (SocialCom
, 2010
"... Abstract — Retweeting is the key mechanism for information diffusion in Twitter. It emerged as a simple yet powerful way of disseminating information in the Twitter social network. Even though a lot of information is shared in Twitter, little is known yet about how and why certain information spread ..."
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Cited by 133 (2 self)
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not predict retweetability of a user’s tweet. We believe that this research would inform the design of sensemaking and analytics tools for social media streams. Keywords-Twitter; retweet; tweet; follower; social network; social media; factor analysis I.
Learning Sentiment-Specific Word Embedding for Twitter Sentiment Classification∗
"... We present a method that learns word em-bedding for Twitter sentiment classifica-tion in this paper. Most existing algorithm-s for learning continuous word represen-tations typically only model the syntactic context of words but ignore the sentimen-t of text. This is problematic for senti-ment analy ..."
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. Specif-ically, we develop three neural networks to effectively incorporate the supervision from sentiment polarity of text (e.g. sen-tences or tweets) in their loss function-s. To obtain large scale training corpora, we learn the sentiment-specific word em-bedding from massive distant-supervised tweets
Results 1 - 10
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299