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Building a Twitter opinion lexicon from automatically-annotated tweets

Felipe Bravo-Marquez, Eibe Frank, Bernhard Pfahringer
2016 Knowledge-Based Systems  
Additionally, we show that lexicons created with our method achieve significant improvements over SentiWordNet for classifying tweets into polarity classes, and also outperform SentiStrength in the majority  ...  The expanded lexicon contains part-of-speech (POS) disambiguated entries with a probability distribution for positive, negative, and neutral polarity classes, similarly to SentiWordNet.  ...  In [38] , each concept on ConceptNet is given a sentiment score using iterative regressions that are then propagated via random walks.  ... 
doi:10.1016/j.knosys.2016.05.018 fatcat:kwzxxxwvi5c5xbydwx4mkkk2ze

Sentiment Analysis and Topic Modeling on Tweets about Online Education during COVID-19

Muhammad Mujahid, Ernesto Lee, Furqan Rustam, Patrick Bernard Washington, Saleem Ullah, Aijaz Ahmad Reshi, Imran Ashraf
2021 Applied Sciences  
Keeping in view the adequacy and efficacy of machine learning models, this study adopts TextBlob, VADER (Valence Aware Dictionary for Sentiment Reasoning), and SentiWordNet to analyze the polarity and  ...  Due to the rise of social media as an important mode of communication recently, people's views can be found on platforms such as Twitter, Instagram, Facebook, etc.  ...  The criterion used for defining the sentiment of a tweet based on its polarity score is shown in Table 3 with sample tweets and assigned sentiment.  ... 
doi:10.3390/app11188438 fatcat:pnd53qulpfclropcwbb65y3lza

Unsupervised Opinion Polarity Detection based on New Lexical Resources

Mario Amores, Leticia Arco, Claudia Borroto
2016 Journal of Computacion y Sistemas  
In this paper, we focus on unsupervised polarity detection using lexical resources.  ...  There are polarity detection techniques based on the lexicon of opinion words and those based on machine learning techniques.  ...  By combining a random walk algorithm that weights synsets from the text with polarity scores provided by SentiWordNet, it is possible to build a system comparable to an SVM based supervised approach in  ... 
doi:10.13053/cys-20-2-2318 fatcat:o626bld3t5em7cxw4phruigeki

The Impact of Sentiment Features on the Sentiment Polarity Classification in Persian Reviews

Ehsan Asgarian, Mohsen Kahani, Shahla Sharifi
2017 Cognitive Computation  
For this purpose, a comprehensive Persian WordNet (FerdowsNet), with high recall and proper precision (based on Princeton WordNet), was developed.  ...  This paper investigates the impact of NLP tools, various sentiment features, and sentiment lexicon generation approaches to sentiment polarity classification of internet reviews written in Persian language  ...  The initial version (SentiWordNet v1.0) was improved in SentiWordNet v3.0 using the iterative random walk algorithm and WordNet 3.0 graph [49] .  ... 
doi:10.1007/s12559-017-9513-1 fatcat:ps37e3ln5zcnpdxkq7p7yfhrca

Reputation analysis with a ranked sentiment-lexicon

Filipa Peleja, João Santos, João Magalhães
2014 Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval - SIGIR '14  
This analysis leverages on a sentiment lexicon that includes general sentiment words and domain specific jargon.  ...  For example, in the movies domain it is not uncommon to see reviews citing Batman or Anthony Hopkins as esteemed references.  ...  In parallel, results for the polarity task shows that the associated weights for the sentiment words perform well on standard binary polarity evaluation.  ... 
doi:10.1145/2600428.2609546 dblp:conf/sigir/PelejaSM14 fatcat:gphhcz77nbapznwj6ctx2un4ue

Applying Deep Learning Techniques for Sentiment Analysis to Assess Sustainable Transport

Ainhoa Serna, Aitor Soroa, Rodrigo Agerri
2021 Sustainability  
In this work we have leveraged such User Generated Content to obtain a high accuracy sentiment analysis model which automatically analyses the negative and positive opinions expressed in the transport  ...  Users voluntarily generate large amounts of textual content by expressing their opinions, in social media and specialized portals, on every possible issue, including transport and sustainability.  ...  Table 6 . 6 Linguistic analysis for polarity classification with SentiWordNet. Table 7 . 7 XLM-RoBERTa results on multiclass classification.  ... 
doi:10.3390/su13042397 fatcat:47reizsjbzg2bdk6maahmxstlu

An Empirical Approach for Extreme Behavior Identification through Tweets Using Machine Learning

Sharif, Mumtaz, Shafiq, Riaz, Ali, Husnain, Choi
2019 Applied Sciences  
It is pertinent to mention that this is the novel reported research work in the context of Afghanistan war zone for Twitter content analysis using machine learning methods.  ...  Furthermore, the classification algorithms like naïve Bayes', K Nearest Neighbors (KNN), random forest, Support Vector Machine (SVM) and ensemble classification methods (with bagging and boosting), etc  ...  Data Collection and Preparation Many Twitter-based datasets are available over the internet either freely or commercially for understanding public sentiment on social or political issues [39, 40] .  ... 
doi:10.3390/app9183723 fatcat:i7x37l2nbjdqjj5ftm44dtnrii

Mutually Enhancing Community Detection and Sentiment Analysis on Twitter Networks

William Deitrick, Wei Hu
2013 Journal of Data Analysis and Information Processing  
This study presents a novel twist on two popular techniques for studying OSNs: community detection and sentiment analysis.  ...  The Twitter networks used for this study are extracted from four accounts related to Microsoft Corporation, and together encompass more than 60,000 users and 2 million tweets collected over a period of  ...  The Infomap algorithm, on the other hand, models information flow in a network using the probabilities of particular random walks within the network.  ... 
doi:10.4236/jdaip.2013.13004 fatcat:xe5avoshuvhenfnp3oavd27zte

Arabic Sentiment Classification using MLP Network Hybrid with Naive Bayes Algorithm

Mohammad Subhi Al-Batah, Shakir Mrayyen, Malek Alzaqebah
2018 Journal of Computer Science  
The datasets are then classified into positive or negative polarities of sentiment using both standard and combined system. The 10-fold cross validation was employed for splitting the dataset.  ...  Sentiment analysis techniques are increasingly exploited to categorize the opinion text to one or more predefined sentiment classes for the creation and automated maintenance of review-aggregation websites  ...  Ethics We testify that our research paper submitted to the Journal of Science Publication, title: Investigation of Naive Bayes Combined with Multilayer Perceptron for Arabic Sentiment Analysis and Opinion  ... 
doi:10.3844/jcssp.2018.1104.1114 fatcat:t5daxwq6zzccbmsjuaeep2isjq

Establishing News Credibility using Sentiment Analysis on Twitter

Zareen Sharf, Zakia Jalil, Wajiha Amir, Nudrat Siddiqui
2019 International Journal of Advanced Computer Science and Applications  
An area-specific analysis is done to determine the polarity of extracted tweets for make an automatic classification that what recent news people have liked or disliked.  ...  The research is further extended to perform retweet analysis to describe the re-distribution of reactions on a specific twitter post (or tweet).  ...  For this purpose, SentiWordNet scores were combined with a random walk analysis of the concepts found in the text over the WordNet graph.  ... 
doi:10.14569/ijacsa.2019.0100927 fatcat:a72n2hxzbvgozerfx5ixz3as7i

A Semantic Conceptualization using Tagged Bag-of-Concepts for Sentiment Analysis

Yassin S. Mehanna, M. Mahmuddin
2021 IEEE Access  
In this study, a semantic conceptualization method using tagged bag-of-concepts for SA is proposed to detect the correct sentiment towards the actual target entity that considers all affective and conceptual  ...  The proposed solution has been applied on two datasets from the restaurant domain, sentiment analysis is performed using the TBoCs structure on multiple levels including document, aspect, aspect-category  ...  SentiWordNet generic sentiment lexicon and domain-specific sentiment lexicon were used for polarity detection.  ... 
doi:10.1109/access.2021.3107237 fatcat:2kjmloselvgn5mmrfgt4xifjf4

Language Independent Sentiment Analysis with Sentiment-Specific Word Embeddings

Carl Saroufim, Akram Almatarky, Mohammad Abdel Hady
2018 Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis  
We were able to achieve a performance improvement by using SSWE over Word2Vec. We also used a graph-based approach for label propagation to auto-generate a sentiment lexicon.  ...  We present a language independent method to train a sentiment polarity model with limited amount of manuallylabeled data.  ...  Using a short list of "seed words" for positive and negative polarities, sentiment is propagated through the network through a random walk method.  ... 
doi:10.18653/v1/w18-6204 dblp:conf/wassa/SaroufimAA18 fatcat:snygald7yzableupt5cgetqnxu

Drug Reaction Discriminator within Encoder-Decoder Neural Network Model: COVID-19 Pandemic Case Study

Hanane Grissette, El Habib Nfaoui
2020 2020 Seventh International Conference on Social Networks Analysis, Management and Security (SNAMS)  
Few approaches have proposed in this matter, especially for detecting different drug reaction descriptions from patients generated narratives on social networks.  ...  In particular, many health-related organizations used sentiment analysis to automatically reporting treatment issues, drug misuse, new infectious disease symptoms.  ...  It also provides sentiment scores of positive, negative scores for each word, by using semisupervised learning, automatic annotation of WordNet, and a random-walk approach. • AFINN [18] : the AFINN lexicon  ... 
doi:10.1109/snams52053.2020.9336561 fatcat:co7uqgtuunaixnd5tunorkqsd4

Automatic Generation of Word-Emotion Lexicon for Multiple Sentiment Polarities on Social Media Texts

Liza Wikarsa, Minsoo Kim
2019 ICIC Express Letters  
Due to the limitations of general lexicons as resources for evaluating the sentiment of a text passage, this study proposes a framework to generate an automated word-emotion lexicon on Twitter by searching  ...  This expanded lexicon is useful for performing domain specific tasks on social media texts.  ...  An appreciation is also given to Faculty of Engineering, University Katolik De La Salle Manado, Indonesia, for the support and encouragement.  ... 
doi:10.24507/icicel.13.04.317 fatcat:bn7yvmnbqfdddatsffbrmngixq

A Survey on sentiment analysis in Persian: A Comprehensive System Perspective Covering Challenges and Advances in Resources, and Methods [article]

Zeinab Rajabi, MohammadReza Valavi
2021 arXiv   pre-print
for future research on Persian texts.  ...  Then, a detailed survey of the sentiment analysis methods used for Persian texts is presented, and previous relevant works on Persian Language are discussed.  ...  Semantic network interconnected Persian graph to English graph and utilized random walk algorithm for determining the polarity of Persian words.  ... 
arXiv:2104.14751v1 fatcat:ftt5inmi6ngvnngneyc2rp25by
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