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
core +2 more sources
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
core +1 more source
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
core +3 more sources
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.
core +2 more sources
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
core +2 more sources
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
core +2 more sources
Sentiment Lexicon Adaptation with Context and Semantics for the Social Web [PDF]
, 2017 Sentiment analysis over social streams offers governments and organisations a fast and effective way to monitor the publics' feelings towards policies, brands, business, etc.
Bollen +7 more
core +1 more source
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
core +2 more sources
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
core +1 more source
Better Document-level Sentiment Analysis from RST Discourse Parsing [PDF]
, 2015 Discourse structure is the hidden link between surface features and document-level properties, such as sentiment polarity. We show that the discourse analyses produced by Rhetorical Structure Theory (RST) parsers can improve document-level sentiment ...
Bhatia, Parminder +2 more
core +1 more source