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Sentiment Analysis Using Deep Learning Techniques: A Review

Qurat Tul, Mubashir Ali, Amna Riaz, Amna Noureen, Muhammad Kamranz, Babar Hayat, A. Rehman
2017 International Journal of Advanced Computer Science and Applications  
This Review Paper highlights latest studies regarding the implementation of deep learning models such as deep neural networks, convolutional neural networks and many more for solving different problems  ...  , brands, and politics.  ...  This contribution [43] proposed a data driven supervised approach for the purpose of feature reduction and development of lexicon specific to twitter sentiment analysis about brand.  ... 
doi:10.14569/ijacsa.2017.080657 fatcat:us4hwclsx5ghtjo4v5vkvfkqqm

Sentiment Analysis using Artificial Neural Network

2020 International journal of recent technology and engineering  
The paper presents a survey with main focus on performance of different artificial neural networks used for opinion mining or sentiment analysis while it also includes various machine learning approaches  ...  Analysis of public sentiments deals with the determination of the polarity of different public opinions or reviews into either the category of positive, negative or neutral.  ...  Then, the targeted approach of twitter sentiment analysis was further enhanced by Ghiassi et al. [13] in 2016 itself that used supervised feature engineering and artificial neural network.  ... 
doi:10.35940/ijrte.e6450.018520 fatcat:vyee4yzojje3bf7cm3zesm3k7i

Neural Network Based Context Sensitive Sentiment Analysis

S. Suruthi, M. Pradeeba, A. Sumaiya, J.I Sheeba
2015 International Journal of Computer Applications Technology and Research  
This paper is based on sentiment classification using Competitive layer neural networks and classifies the polarity of a given text whether the expressed opinion in the text is positive or negative or  ...  The conversation and the posts available in social media are unstructured in nature. So sentiment analysis will be a challenging work in this platform.  ...  Twitter brand sentiment analysis: A hybrid system using ngram analysis and dynamic artificial neural network makes several contributions to twitter sentiment analysis, demonstrated through application  ... 
doi:10.7753/ijcatr0403.1004 fatcat:ozmn7oxktrghlgic4mgqb4pnga

Twitter brand sentiment analysis: A hybrid system using n-gram analysis and dynamic artificial neural network

M. Ghiassi, J. Skinner, D. Zimbra
2013 Expert systems with applications  
In this research, we introduce an approach to supervised feature reduction using n-grams and statistical analysis to develop a Twitter-specific lexicon for sentiment analysis.  ...  The existing literature on Twitter sentiment analysis uses various feature sets and methods, many of which are adapted from more traditional text classification problems.  ...  The use of a highly explanatory Twitter-specific lexicon in this research demonstrated that it offered capabilities for the Justin Bieber brand to recognize emerging issues with their brand identity.  ... 
doi:10.1016/j.eswa.2013.05.057 fatcat:wjodhhyps5givfbpmbr6e6bwca

Systematic reviews in sentiment analysis: a tertiary study

Alexander Ligthart, Cagatay Catal, Bedir Tekinerdogan
2021 Artificial Intelligence Review  
Different features, algorithms, and datasets used in sentiment analysis models are mapped.  ...  According to this analysis, LSTM and CNN algorithms are the most used deep learning algorithms for sentiment analysis.  ...  Han et al. (2019) developed a semi-supervised model using dynamic thresholding and multiple classifiers for sentiment analysis.  ... 
doi:10.1007/s10462-021-09973-3 fatcat:zo7igc4fnnh47kyafncbfmaf3u

IMAGE SENTIMENTAL ANALYSIS: AN OVERVIEW

Vedashree C.R and Sowmyashree S. V. Sunil Kumar
2022 Zenodo  
On social networking sites, images are the simplest way for people to communicate their emotions.  ...  This paper introduces the area of Image Sentiment Analysis and examines the issues that it raises.  ...  For textual sentiment analysis, they use a CNN built on top of pre-trained word vectors, and for visual sentiment analysis, they use a deep convolution neural network (DNN) with generalized dropout.  ... 
doi:10.5281/zenodo.6507385 fatcat:t4ppdghzlvg2neswfsfovbvoai

A Review on Text-Based Emotion Detection – Techniques, Applications, Datasets, and Future Directions [article]

Sheetal Kusal, Shruti Patil, Jyoti Choudrie, Ketan Kotecha, Deepali Vora, Ilias Pappas
2022 arXiv   pre-print
Artificial Intelligence (AI) has been used for processing data to make decisions, interact with humans, and understand their feelings and emotions.  ...  It also reviews the different applications of TBED across various research domains and highlights its use.  ...  (Su et al. 2021 ) the authors proposed an approach to automatically train attention supervision information for neural Aspect based sentiment analysis.  ... 
arXiv:2205.03235v1 fatcat:b3m25fg6xfc3leeym22eqysq5a

Survey of Tools and Techniques for Sentiment Analysis of Social Networking Data

Sangeeta Rani, Nasib Singh, Preeti Gulia
2021 International Journal of Advanced Computer Science and Applications  
This paper presents a systematic survey related to Social Networking Sites Sentiment Analysis and mainly focus on Twitter sentiment analysis.  ...  Twitter is one of the social media platforms that are widely explored in the area of sentiment analysis.  ...  [3] proposed twitter sentiment analysis by using POS specific polarity features and explored tree kernels to prevent the need for tedious feature engineering. 11,875 manually labeled tweets publically  ... 
doi:10.14569/ijacsa.2021.0120430 fatcat:kccjxxwia5gmfpwixmemza2oqm

A Survey on Deep Learning in Big Data and its Applications [article]

Zair Bouzidi, Mourad Amad, Abdelmalek Boudries
2021 figshare.com  
Abstract: Individuals can exchange real-time information thanks to the vast spread and reach of social networks.  ...  This active participation with the corporate data, as emails, documents, databases, business processor history, etc and content published on the Web, as age and contact details, reviews, comments, photos  ...  Researchers employ a mixed architecture consisting of a convolutional neural network (CNN) integrated with an artificial neural network (ANN) to perform French energy demand predictions using weather data  ... 
doi:10.6084/m9.figshare.14737953.v1 fatcat:sadrsu25g5dmbbjturvh72wgde

A Survey on Deep Learning in Big Data and its Applications [article]

Zair Bouzidi, Mourad Amad, Abdelmalek Boudries
2021 figshare.com  
Abstract: Individuals can exchange real-time information thanks to the vast spread and reach of social networks.  ...  This active participation with the corporate data, as emails, documents, databases, business processor history, etc and content published on the Web, as age and contact details, reviews, comments, photos  ...  Researchers employ a mixed architecture consisting of a convolutional neural network (CNN) integrated with an artificial neural network (ANN) to perform French energy demand predictions using weather data  ... 
doi:10.6084/m9.figshare.14737953.v2 fatcat:l4fzcr4fpfevxpcpwbnwvevvpa

Evaluation of Sentiment Analysis in Finance: From Lexicons to Transformers

Kostadin Mishev, Ana Gjorgjevikj, Irena Vodenska, Lubomir T. Chitkushev, Dimitar Trajanov
2020 IEEE Access  
We start the evaluation with specific lexicons for sentiment analysis in finance and gradually build the study to include word and sentence encoders, up to the latest available NLP transformers.  ...  Sentiment analysis models can provide an efficient method for extracting actionable signals from the news.  ...  Additionally, paragraph vectors can be used as features for the paragraph, which can be fed as input to a classifier or to a neural network, making them appropriate for evaluation of sentiment analysis  ... 
doi:10.1109/access.2020.3009626 fatcat:efvchm5chbgibfzuhw7zjmh7ii

A Literature Review on Application of Sentiment Analysis Using Machine Learning Techniques

Anvar Shathik J, Krishna Prasad K
2020 Zenodo  
Many businesses are using social media networks to deliver different services and connect with clients and collect information about the thoughts and views of individuals.  ...  Finally, this paper includes a research proposal for e-commerce environment towards sentiment analysis applying machine learning algorithms.  ...  It uses a dynamic neural network architecture (DAN2) and SVM as calculated by the reminder, accuracy and F1 metrics The outcome proved that the Twitter Generic Feature Set (TGFS) extracts from 2 different  ... 
doi:10.5281/zenodo.3977576 fatcat:djsvzgiypnfibcvj6swo3pw75u

A Precisely Xtreme-Multi Channel Hybrid Approach For Roman Urdu Sentiment Analysis

Faiza Mehmood, Muhammad Usman Ghani, Muhammad Ali Ibrahim, Rehab Shahzadi, Waqar Mahmood, Muhammad Nabeel Asim
2020 IEEE Access  
underlay corpus features which may eventually improve the performance of target task instead of solely relying on standalone neural word embeddings and automated feature engineering performed by deep  ...  STATE-OF-THE-ART MACHINE AND DEEP LEARNING WORK FOR ROMAN URDU SENTIMENT ANALYSIS Sentiment analysis is the core building block behind the development of more appealing marketing and branding strategies  ...  For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/ developed experimental dataset will be publicly available.  ... 
doi:10.1109/access.2020.3030885 fatcat:74xtllokurhfjdzpjg2ispgaxq

Developing a Model for Sentiment Analysis Technique in the field of Tourism using Deep Learning

2020 International journal of recent technology and engineering  
This paper provides a platform for analyzing and summarizing the sentiments expressed by users or customers in the field of online tourism.  ...  The proposed system filters tourism online reviews and classifies them using sentimental technique with the help of deep learning technique.  ...  authors mentioned in this paper gives results that implementation of sentiment analysis in the field of tourism using latest neural network based technique called deep learning will be highly efficient  ... 
doi:10.35940/ijrte.f7390.038620 fatcat:fsgxewmn2jdr3linqptws4yd7y

Over a Decade of Social Opinion Mining [article]

Keith Cortis, Brian Davis
2020 arXiv   pre-print
Social media popularity and importance is on the increase, due to people using it for various types of social interaction across multiple channels.  ...  This contributes towards the evolution of Artificial Intelligence, which in turn helps the advancement of several real-world use cases, such as customer service and decision making.  ...  -used in 1 study [478] ; • Hierarchical Attention Network, a neural architecture for document classification [541] , used in 1 study [152] .  ... 
arXiv:2012.03091v1 fatcat:bm5nydbdvbalzi33l3w2ivkdja
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