Robust Image Sentiment Analysis Using Progressively Trained and Domain Transferred Deep Networks [PDF]
, 2015 Sentiment analysis of online user generated content is important for many social media analytics tasks. Researchers have largely relied on textual sentiment analysis to develop systems to predict political elections, measure economic indicators, and so ...
Jin, Hailin +3 more
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Econometrics meets sentiment : an overview of methodology and applications [PDF]
, 2020 The advent of massive amounts of textual, audio, and visual data has spurred the development of econometric methodology to transform qualitative sentiment data into quantitative sentiment variables, and to use those variables in an econometric analysis ...
Algaba, Andres +4 more
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Classifying sentiment in microblogs: is brevity an advantage? [PDF]
, 2010 Microblogs as a new textual domain offer a unique proposition for sentiment analysis. Their short document length suggests any sentiment they contain is compact and explicit.
Bermingham, Adam, Smeaton, Alan F.
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Bilingual Sentiment Embeddings: Joint Projection of Sentiment Across Languages [PDF]
, 2018 Sentiment analysis in low-resource languages suffers from a lack of annotated corpora to estimate high-performing models. Machine translation and bilingual word embeddings provide some relief through cross-lingual sentiment approaches.
Barnes, Jeremy +2 more
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The Royal Birth of 2013: Analysing and Visualising Public Sentiment in the UK Using Twitter [PDF]
, 2013 Analysis of information retrieved from microblogging services such as Twitter can provide valuable insight into public sentiment in a geographic region. This insight can be enriched by visualising information in its geographic context.
Barker, Adam +2 more
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Diving Deep into Sentiment: Understanding Fine-tuned CNNs for Visual Sentiment Prediction [PDF]
, 2015 Visual media are powerful means of expressing emotions and sentiments. The constant generation of new content in social networks highlights the need of automated visual sentiment analysis tools. While Convolutional Neural Networks (CNNs) have established
Jiang Y.-G. +6 more
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, 2017 Social networks are the main resources to gather information about people’s opinion and sentiments towards different topics as they spend hours daily on social media and share their opinion. In this technical paper, we show the application of sentimental analysis and how to connect to Twitter and run sentimental analysis queries.
Hamid Bagheri, Md Johirul Islam
openaire +2 more sources
Topic-dependent sentiment analysis of financial blogs [PDF]
, 2009 While most work in sentiment analysis in the financial domain has focused on the use of content from traditional finance news, in this work we concentrate on more subjective sources of information, blogs.
Bermingham, Adam +6 more
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Analyzing Disproportionate Reaction via Comparative Multilingual Targeted Sentiment in Twitter [PDF]
, 2017 Global events such as terrorist attacks are commented upon in social media, such as Twitter, in different languages and from different parts of the world.
Agarwal A. +6 more
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Sentiment analysis of health care tweets: review of the methods used. [PDF]
, 2017 BACKGROUND: Twitter is a microblogging service where users can send and read short 140-character messages called "tweets." There are several unstructured, free-text tweets relating to health care being shared on Twitter, which is becoming a popular area ...
Darzi, A, Gohil, S, Vuik, S
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