Media Text
Branded Media Text as Communicative integration Model of Interaction with Audience
... the media text of a hybrid-communicative form, journalism, marketing, PR and advertising realize similar conceptual tasks: all these types of communication actually sell ideas in order to find out the ...
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Robust part-of-speech tagging of social media text
... social media surfaced (Thurlow et al., 2004). As using social media requires using a technical device, it is often also CMC, ...social media platform but certainly is ...non-standard text with ...
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Aggression Detection on Social Media Text Using Deep Neural Networks
... resents some information about the sequence at every step of the input. In theory, RNNs can learn long dependencies but in practice, they fail to do so and tend to be biased towards the most recent input in the sequence ...
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UTCNN: a Deep Learning Model of Stance Classification on Social Media Text
... Among all UTCNN variations, we find that user information is most important, followed by topic and comment information. UTCNN without user information shows results similar to SVMs — it does well for Sup and Neu but ...
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Sentence Boundary Detection for Social Media Text
... social media text and is based on comparing three machine learning algorithms — Conditional Random Fields, Naïve Bayes and Sequential Minimal Optimization — to a rule-based system, also with the rule-based ...
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Part of speech Tagging of Code Mixed Social Media Text
... code-mixed text was developed by Solorio and Liu ...English-Spanish text by us- ing existing monolingual POS taggers for both the ...social media text and hence the difficulties were ...
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Normalization of Social Media Text using Deep Neural Networks
... social media, creativ- ity and individuality, which has created problems at two ...social media text is often un- suitable for various Natural Language Processing (NLP) tasks, such as Information ...
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A Beam Search Decoder for Normalization of Social Media Text with Application to Machine Translation
... social media text nor- malization in the context of machine translation, so research on machine translation of social media text is relevant to our ...social media text transla- ...
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A K Competitive Autoencoder for Aggression Detection in Social Media Text
... each text was to be classified either as aggressive or ...social media text is classified into three categories, hate speech, aggressive text and ...social media posts due to their ...
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Modeling Factuality Judgments in Social Media Text
... search, which focuses on quoted statements in so- cial media text. de Marneffe et al. (2012) conduct an empirical evaluation of FactBank ratings from Mechanical Turk workers, finding a high degree of ...
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Towards Normalising Konkani English Code Mixed Social Media Text
... We also present word-level language iden- tification experiments are performed us- ing this dataset. Different techniques are employed, including a simple unsu- pervised dictionary-based approach, su- pervised word-level ...
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How Noisy Social Media Text, How Diffrnt Social Media Sources?
... dia text being “noisy” (Java, 2007; Becker et ...social media text is more noisy than conventional, edited text ...social media comes in many flavours — including microblogs, blogs, and ...
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Social Media Text Classification under Negative Covariate Shift
... which forms the negative data. n is usually large. However, due to the labor-intensive effort of manual labeling, the user can label only a certain number of training posts. Then the labeled nega- tive training posts may ...
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Epidemiological Disease Surveillance Using Public Media Text Mining.
... Lu et. al. developed a visual analytics framework, which is directly related to EventRiver. This framework allows analysts to visually explore how online news, blogs, social media and other media documents ...
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Language Identification and Analysis of Code Switched Social Media Text
... ing of code-switched text and report comparison of different language identification systems. The best system from the second iteration of these shared tasks uses a logistic regression model and reports a ...
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Document-based Topic Coherence Measures for News Media Text
... news media, two typical use cases are media agenda (McCombs & Shaw, 1972) and news framing (Entman, 1993) ...of media agenda and public agenda ...for media agenda analysis con- sisting of ...
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Real Time analysis of social media text using stream computing
... 4 In above data flow diagram of system, system create connections with twitter streaming api. After that, tweets are fetched in system. Tweets then processed by CEP engine by searching specific keyword in it. Tweets with ...
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EmotionX SmartDubai NLP: Detecting User Emotions In Social Media Text
... In data normalization step we have mainly focused on cleaning the utterance to improve the performance of the model. We have created the custom list of words to replace the internet slang tokens with proper words and the ...
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Identifying the Authors’ National Variety of English in Social Media Text
... In this paper, we present a study for the identification of authors’ national variety of English in texts from social media. In data from Facebook and Twitter, informa- tion about the author’s social profile is ...
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Detection of Stance Related Characteristics in Social Media Text
... specific text type (blog posts and comments) towards a specific thematic area (2016 UK ...of text chunks covering a wider thematic ...other text data ...
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