Deep Learning Publication Navigator - subtopic: twitter


Year TitleAuthor
2017   CNN for situations understanding based on sentiment analysis of twitter data  S Liao, J Wang, R Yu, K Sato, Z Cheng
2017   An Efficient Deep Neural Architecture for Multilingual Sentiment Analysis in Twitter  W Becker, J Wehrmann, HEL Cagnini, RC Barros
2017   A Deep Multi-View Learning Framework for City Event Extraction from Twitter Data Streams  N Farajidavar, S Kolozali, P Barnaghi
2017   Determining Ethnicity of Immigrants using Twitter Data  M Saravanan
2017   Dialogue Processing on Twitter  S JAFARI, A OLUOKUN
2017   A Characterization Study of Arabic Twitter Data with a Benchmarking for State-of-the-Art Opinion Mining Models  R Baly, G Badaro, G El
2017   Using Cognitive Computing to Get Insights on Personality Traits from Twitter Messages  RAP Junior, D Inkpen
2017   Part-of-Speech Tagging for Twitter with Adversarial Neural Networks  T Gui, Q Zhang, H Huang, M Peng, X Huang
2017   Amobee at SemEval-2017 Task 4: Deep Learning System for Sentiment Detection on Twitter  A Rozental, D Fleischer
2017   Are Deep Learning Methods Better for Twitter Sentiment Analysis?  Y Lu, K Sakamoto, H Shibuki, T Mori
2017   A character-based convolutional neural network for language-agnostic Twitter sentiment analysis  J Wehrmann, W Becker, HEL Cagnini, RC Barros
2016   Finki at SemEval-2016 Task 4: Deep Learning Architecture for Twitter Sentiment Analysis  D Stojanovski, G Strezoski, G Madjarov, I Dimitrovski
2016   ASU: An Experimental Study on Applying Deep Learning in Twitter Named Entity Recognition  MN Gerguis, C Salama, MW El
2016   LyS at SemEval-2016 Task 4: Exploiting Neural Activation Values for Twitter Sentiment Classification and Quantification  D Vilaresa, Y Dovala, MA Alonsoa
2016   Exploiting Twitter Moods to Boost Financial Trend Prediction Based on Deep Network Models  Y Huang, K Huang, Y Wang, H Zhang, J Guan, S Zhou
2016   Detecting and Analyzing Bursty Events on Twitter  PPH Kung
2016   Twitter spam detection based on deep learning  T Wu, S Liu, J Zhang, Y Xiang
2016   PotTS at SemEval-2016 Task 4: Sentiment Analysis of Twitter Using Character-level Convolutional Neural Networks.  U Sidarenka, KL Straße
2016   Recurrent Neural Networks for Customer Purchase Prediction on Twitter  M Korpusik, S Sakaki, FCYY Chen
2015   Shared tasks of the 2015 workshop on noisy user-generated text: Twitter lexical normalization and named entity recognition  T Baldwin, MC de Marneffe, B Han, YB Kim, A Ritter
2015   Prediction of changes in the stock market using twitter and sentiment analysis  IV Serban, DS González, X Wu
2015   Twitter Sentiment Analysis Using Deep Convolutional Neural Network  D Stojanovski, G Strezoski, G Madjarov, I Dimitrovski
2015   Detecting and Disambiguating Locations Mentioned in Twitter Messages  D Inkpen, J Liu, A Farzindar, F Kazemi, D Ghazi
2015   Exploring co-learning behavior of conference participants with visual network analysis of Twitter data  H Aramo