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"Twitter Sentiment in Data Streams with Perceptron"
written by Nathan Aston, Jacob Liddle, Wei Hu,
published by Journal of Computer and Communications, Vol.2 No.3, 2014
has been cited by the following article(s):
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  • CrossRef
[1] 1W A bibliometric analysis on tourist destinations research
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[2] A typology of viral ad sharers using sentiment analysis
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[3] Sentimental Analysis of Demonetization Over Twitter Data Using Machine Learning
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[4] Evaluating Active Learning Sampling Strategies for Opinion Mining in Brazilian Politics Corpora
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[5] Basic Review of Different Strategies for Sentiment Analysis in Online Social Networks
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[6] Opinion Mining and Active Learning: a Comparison of Sampling Strategies
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[7] An Optimized Hybrid Neural Network Model for Detecting Depression among Twitter Users
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[8] Complex industrial automation data stream mining algorithm based on random Internet of robotic things
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[9] Clinical Communication and Collaboration: Three Essays Examining the Impact of IT Interventions on At-Risk Populations Using Healthcare Analytics
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[10] Multilingual Sentiment Analysis for a Swiss Gig
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[11] BrainT at IEST 2018: Fine-tuning Multiclass Perceptron For Implicit Emotion Classification
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[12] Análise de sentimento em tweets
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[13] A Review of Sentiment Semantic Analysis Technology and Progress
2017
[14] The Use of Hashtags in the Promotion of Art Exhibitions
2017
[15] Influência dos sentimentos dos turistas nos social media para o desenvolvimento do turismo
2016
[16] Like it or not: A survey of twitter sentiment analysis methods
ACM Computing Surveys (CSUR), 2016
[17] Smart Card Adoption in Healthcare: An Experimental Survey Design using Message Framing
2016
[18] Design and simulation of a novel classification framework for separating sentiment from assorted game related tweets
2016
[19] Design of Machine Learning Approach For Spam Tweet Detection
IJARIIE, 2016
[20] Tourist Clusters, Destinations and Competitiveness: Theoretical Issues and Empirical Evidences
2015
[21] Understanding and monitoring attitudes of product properties over time
Dissertation, 2015
[22] A bibliometric analysis on tourist destinations research: focus on destination management and tourist cluster
2015
[23] A bibliometrics analysis on tourist destinations research
2015
[24] A trust-based sentiment delivering calculation method in microblog
International Journal of Services Technology and Management, 2015
[25] 1 A bibliometric analysis on tourist destinations research
Tourist Clusters, Destinations and Competitiveness: Theoretical Issues and Empirical Evidences, 2015
[26] Tourist Clusters, Destinations and Competitiveness
2015
[27] 大数据分析中的计算智能研究现状与展望
META, 2015
[28] A era de um mercado social
2015
[29] Talking about Climate Change and Global Warming
PloS one, 2015
[30] # Worldcup2014 on Twitter
Computational Science and Its Applications -- ICCSA 2015, 2015
[31] Content-Based Sentiment and Geolocation Tagging of Social Media Messages for Trend Analysis
The Fifth International Workshop on Mining Ubiquitous and Social Environments. 2014., 2014
[32] Corpus-Based Information Extraction and Opinion Mining for the Restaurant Recommendation System
Statistical Language and Speech Processing. Springer International Publishing,, 2014
[33] Sentiment Analysis on the Social Networks Using Stream Algorithms
Journal of Data Analysis and Information Processing, 2014
[34] Real-Time Analysis of Online Product Reviews by Means of Multi-Layer Feed-Forward Neural Networks
2014
[35] The State-of-the-Art in Twitter Sentiment Analysis: A Review and Benchmark Evaluation
2010
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