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Feature Extraction and Classification of Movie Reviews

Nhamo Mtetwa, Awukam Ojang Awukam, Mehdi Yousefi
2018 2018 5th International Conference on Soft Computing & Machine Intelligence (ISCMI)  
We investigate the effect of feature extraction techniques on supervised machine learning classifiers using four different performance metrics using a publicly available movie review dataset.  ...  Sentiment analysis identifies a user's attitude towards a service, a topic or an event and it is very useful for companies that receive many written reviews of their services.  ...  Before classification of text sentiment, the plain text documents need to be transformed into features for machine learning classification of the sentiments as positive or negative.  ... 
doi:10.1109/iscmi.2018.8703235 fatcat:kkaod37uujhopofdseqn4u3xze

A Systematic Survey of Online Data Mining Technology Intended for Law Enforcement

Matthew Edwards, Awais Rashid, Paul Rayson
2015 ACM Computing Surveys  
As more and more crime takes on a digital aspect, law enforcement bodies must tackle an online environment generating huge volumes of data.  ...  This article remedies this gap through a systematic mapping study describing online data mining literature which visibly targets law enforcement applications, using evidence-based practices in survey-making  ...  The other identification studies using machine learning more generally address the identification of criminals from email data.  ... 
doi:10.1145/2811403 fatcat:qpvfebejpfgp5bh3cgykaoumze

Text Analysis of User-Generated Contents for Health-care Applications - Case Study on Smoking Status Classification

Deema Abdal Hafeth, Amr Ahmed, David Cobham
2014 Proceedings of the International Conference on Knowledge Discovery and Information Retrieval  
Based on analyzing the properties of UGC, we propose the use of Linguistic Inquiry Word Count (LIWC) an approach being used for the first time for such a health-related task.  ...  In this paper, we present an investigation of text analysis for smoking status classification from User-Generated Contents (UGC), such as online forum discussions.  ...  This changes the input data from unstructured text space into features vector space;  Model building phase: includes the use of a suitable machine learning algorithm classifier that produces a useful  ... 
doi:10.5220/0005080502420249 dblp:conf/ic3k/HafethAC14 fatcat:bsu52wpexjhebi3fezunazg6ni

Emotion Detection in Text: a Review [article]

Armin Seyeditabari, Narges Tabari, Wlodek Zadrozny
2018 arXiv   pre-print
Although, there is an essential need to improve the design and architecture of current systems, factors such as the complexity of human emotions, and the use of implicit and metaphorical language in expressing  ...  In this paper, we review the work that has been done in identifying emotion expressions in text and argue that although many techniques, methodologies, and models have been created to detect emotion in  ...  Facing the problem of lack of labeled emotional text, created a large dataset (about 2.5 million tweets) using emotion related hashtags, and used two machine learning algorithms for emotion identification  ... 
arXiv:1806.00674v1 fatcat:gz6kimtt2vh77clq2loky3vza4

Applying machine learning EEG signal classification to emotion‑related brain anticipatory activity

Marco Bilucaglia, Gian Marco Duma, Giovanni Mento, Luca Semenzato, Patrizio E. Tressoldi
2021 F1000Research  
Considering the relevance of emotion in human cognition and behaviour, an important application of machine learning has been found in the field of emotion identification based on neurophysiological activity  ...  The present work aims to provide new methodological insight into machine learning applied to emotion identification based on electrophysiological brain activity.  ...  A machine learning-based investigation utilizing the in-text features for the identification of dominant emotion in an email 2.  ... 
doi:10.12688/f1000research.22202.3 fatcat:wzjwuoa2bnayhkslmws4xmt7t4

Fake News Detection of COVID-19 on Twitter Platform: A Review

Dr. Hamid Ghous Khansa Rana
2021 Zenodo  
In fake news identification, the effect of linguistic features and contextual characteristics areanalysed and some techniques such as Naive Bayes, Decision tree, Hybrid CNN, KNN, and SVMare compared.  ...  The goal of this research is to examine the false news on the Twitter platform connected to COVID-19. A difficult task for humans is to recognize such false facts.  ...  Preprocessing is done with email sentiment analysis and text-based gossip identification.  ... 
doi:10.5281/zenodo.4536673 fatcat:vqci2b66ovg5znmfzbcvigh3tm

Mood Detection Based on Arabic Text Documents using Machine Learning Methods

Abdelbaset Hussein
2020 International Journal of Advanced Trends in Computer Science and Engineering  
Machine learning algorithms allow a practical and beneficial platform for analyzing and detect mood from the text documents.  ...  Document text classification is utilized for information feature extraction and retrieval as the primary source of digitizing the written information using text classification techniques.  ...  [23, 28] presented novel research for emotion detection based on text mining using machine learning approaches.  ... 
doi:10.30534/ijatcse/2020/36942020 fatcat:wcuqjwgtqvhi3ghsfqz34patoa

Applying machine learning EEG signal classification to emotion‑related brain anticipatory activity

Marco Bilucaglia, Gian Marco Duma, Giovanni Mento, Luca Semenzato, Patrizio E. Tressoldi
2021 F1000Research  
Considering the relevance of emotion in human cognition and behaviour, an important application of machine learning has been found in the field of emotion identification based on neurophysiological activity  ...  The present work aims to provide new methodological insight into machine learning applied to emotion identification based on electrophysiological brain activity.  ...  Finally, the main contribution of our results for the scientific community is that they provide a methodological advancement that is generally valid both for the investigation of emotion based on a machine  ... 
doi:10.12688/f1000research.22202.2 fatcat:jnxxvmtlwvh5ja4fxf3fsrmhx4

Emotions in texts

Leeveshkumar Pokhun, M Yasser Chuttur
2020 Bulletin of Social Informatics Theory and Application  
From our analysis and findings, we urge researchers to consider the development of datasets, evaluation benchmarks and a common platform for sharing achievements in emotion analysis to see further development  ...  In this paper, we review different emotion models, emotion datasets and the corresponding techniques used for emotion analysis in past studies.  ...  The dominant tree is then utilized to classify text retrieved from users chat sessions.  ... 
doi:10.31763/businta.v4i2.256 fatcat:znxd24hk7fhklgf2kwpc3m6mru

Online Social Networks and Writing Styles — A Review of the Multidisciplinary Literature

Kah Yee Tai, Jasbir Dhaliwal, Shafiza Mohd Shariff
2020 IEEE Access  
Thus, in this paper, we also propose a novel machine learning prediction model based on tense morphology, to classify age and gender from English blogs, and the PAN 2013 dataset.  ...  In recent years, author identification has become an active research area, where the major differences are caused by paper or online medium, mode of entry and target audience.  ...  people adapt their language to their conversational partners) as a writing style in OSN text in demographics and cybersecurity; and 7) proposed a novel machine learning prediction model based on tense  ... 
doi:10.1109/access.2020.2985916 fatcat:qpejezxkmveyhmpazdz5a3mf7q

Natural Language Processing: State of The Art, Current Trends and Challenges [article]

Diksha Khurana, Aditya Koli, Kiran Khatter, Sukhdev Singh
2017 arXiv   pre-print
It has spread its applications in various fields such as machine translation, email spam detection, information extraction, summarization, medical, and question answering etc.  ...  The paper distinguishes four phases by discussing different levels of NLP and components of Natural Language Generation (NLG) followed by presenting the history and evolution of NLP, state of the art presenting  ...  As for Google, in September 2016, announced a new machine translation system based on Artificial neural networks and Deep learning .  ... 
arXiv:1708.05148v1 fatcat:7dvsgmaslvddhdiy3udohgudky

AI Based Emotion Detection for Textual Big Data: Techniques and Contribution

Sheetal Kusal, Shruti Patil, Ketan Kotecha, Rajanikanth Aluvalu, Vijayakumar Varadarajan
2021 Big Data and Cognitive Computing  
Such crucial insights cannot be completely obtained by doing AI-based big data sentiment analysis; hence, text-based emotion detection using AI in social media big data has become an upcoming area of Natural  ...  The qualitative review represents different emotion models, datasets, algorithms, and application domains of text-based emotion detection.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/bdcc5030043 fatcat:yfdffp7ohzcilijvyai33zk234

Association for Computational Linguistics [chapter]

G. Hirst
2006 Encyclopedia of Language & Linguistics  
We also appreciate and give a special thanks to the support from the Association for Computational Linguistics (ACL). We hope you enjoy reading the memories of the Workshop!  ...  NAACL) has endorsed the event. The lecturers have been invited to write papers on all aspects of computational approaches to Natural Language Processing.  ...  Moreover, in emotional detection systems based on machine learning approach, we have detected that most of these systems use features based on a shallow analysis on the text as: n-grams, punctuation, emoticons  ... 
doi:10.1016/b0-08-044854-2/05234-2 fatcat:bbncnskzhvhxtbfdk5ftli7gva

Understanding the Impact of Emotions on the Quality of Software Artifacts

Khaled M. Khan, Moutaz Saleh
2021 IEEE Access  
This paper proposes a framework for investigating the impact of emotions on the quality of software artifacts and portrays some observations captured during the development of several software engineering  ...  Similarly, negative emotions sometimes result in a positive impact on the quality of artifacts.  ...  MACHINE LEARNING In the machine learning approach, a model is built and trained using a large amount of data before the emotions of test data are classified.  ... 
doi:10.1109/access.2021.3102663 fatcat:plbi4fsidzb5rhyzphaiwspwx4

Fake Reviews Detection: A Survey

Rami Mohawesh, Shuxiang Xu, Son N. Tran, Robert Ollington, Matthew Springer, Yaser Jararweh, Sumbal Maqsood
2021 IEEE Access  
It also summarises and analyses the existing techniques critically to identify gaps based on two groups: traditional statistical machine learning and deep learning methods.  ...  In e-commerce, user reviews can play a significant role in determining the revenue of an organisation. Online users rely on reviews before making decisions about any product and service.  ...  In recent years, machine learning has also been investigated to combat spam, an issue that is expanding to various online applications such as SMS, email, and blogs [132] [133] [134] [135] .  ... 
doi:10.1109/access.2021.3075573 fatcat:p33ialjjjrelfavcpicty44zxy
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