Mobile Sentiment Analysis [PDF]
, 2012 Mobile devices play a significant part in a user’s communication methods and much data that they read and write is received and sent via mobile phones, for instance SMS messages, e-mails, Twitter tweets and social media networking feeds. One of the main goals is to make people aware of how much negative and positive content they read and ...
Chambers, L. +3 more
openaire +4 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
Cross-domain sentiment classification using a sentiment sensitive thesaurus [PDF]
, 2013 Automatic classification of sentiment is important for numerous applications such as opinion mining, opinion summarization, contextual advertising, and market analysis.
Bollegala, Danushka +2 more
core +1 more source
, 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
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
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
core +1 more source
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
Noise or music? Investigating the usefulness of normalisation for robust sentiment analysis on social media data [PDF]
, 2017 In the past decade, sentiment analysis research has thrived, especially on social media. While this data genre is suitable to extract opinions and sentiment, it is known to be noisy.
De Clercq, Orphée +5 more
core +1 more source