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Universal, unsupervised (rule-based), uncovered sentiment analysis

David Vilares, Carlos Gómez-Rodríguez, Miguel A. Alonso
2017 Knowledge-Based Systems  
We present a novel unsupervised approach for multilingual sentiment analysis driven by compositional syntax-based rules.  ...  On the other hand, by introducing the concept of compositional operations and exploiting syntactic information in the form of universal dependencies, we tackle one of their main drawbacks: their rigidity  ...  NLP tools for universal unsupervised SA The following resources serve us as the starting point to carry out state-of-the-art universal, unsupervised and syntactic sentiment analysis.  ... 
doi:10.1016/j.knosys.2016.11.014 fatcat:rjwmda6y7fej5gr6wizsy7gw3e

NLP for Conversations: Sentiment, Summarization, and Group Dynamics

Gabriel Murray, Giuseppe Carenini, Shafiq R. Joty
2018 International Conference on Computational Linguistics  
We will cover unsupervised and supervised approaches, as well as multimodal sentiment detection.  ...  In the second part of the tutorial, we will focus on sentiment analysis and summarization.  ...  NLP applications like machine translation, summarization, and sentiment analysis.  ... 
dblp:conf/coling/MurrayCJ18 fatcat:xcqayosycncghjbaxwmvhnuf4u

sj-pdf-2-jsr-10.1177_10946705211031302 – Supplemental Material for Service Research Priorities: Designing Sustainable Service Ecosystems

Joy M. Field, Darima Fotheringham, Mahesh Subramony, Anders Gustafsson, Amy L. Ostrom, Katherine N. Lemon, Ming-Hui Huang, Janet R. McColl-Kennedy
2021 Figshare  
We employed sentiment analysis to provide more insight into the valence of each topic uncovered in our analysis and, thus, for the specific trend, emerging need, or problem being identified.  ...  Sentiment Analysis Sentiment analysis produces a quantitative score that approximates the positive or negative sentiment in a text.  ...  Maria Golubovskay University of Queensland Australia Teegan Green  ... 
doi:10.25384/sage.16571631.v1 fatcat:iu2he6fxznghfjrnav53jhcg6m

Data Innovation for International Development: An overview of natural language processing for qualitative data analysis [article]

Philipp Broniecki and Anna Hanchar and Slava J. Mikhaylov
2017 arXiv   pre-print
Both traditional interview data and social media analysis can provide rich contextual information and are essential for research, appraisal, monitoring and evaluation.  ...  In this paper, we discuss the potential of using natural language processing to systematize analysis of qualitative data, and to inform quick decision-making in the development context.  ...  Sentiment analysis Instead of uncovering topics, we may want to know of a positive or negative tone of any given document.  ... 
arXiv:1709.05563v1 fatcat:uaabm2donrfqndtltkg7t3rypu

Evaluation of Unsupervised Anomaly Detection Methods in Sentiment Mining

2019 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
In this study, three popular unsupervised anomaly detection algorithms such as density based, statistical based and cluster based anomaly detection methods are evaluated on movie review sentiment mining  ...  Anomaly detection has vital role in data preprocessing and also in the mining of outstanding points for marketing, network sensors, fraud detection, intrusion detection, stock market analysis.  ...  This work proved the applicability and strength of the anomaly detection method through sentiment analysis on movie review sentiment data.  ... 
doi:10.35940/ijitee.i8012.078919 fatcat:spcluqy6obcvth6qtm63rn3i2q

A Review of Machine Learning Approach for Twitter Sentiment Analysis

Mohammed W. Habib, Computer Science Department, College of Science, Al-Nahrain University, Baghdad-Iraq, Zainab N. Sultani, Computer Science Department, College of Science, Al-Nahrain University, Baghdad-Iraq
2021 Al-Nahrain Journal of Science  
The objective of sentiment analysis is to classify sentiment/opinions of users as positive, negative, or neutral from textual data.  ...  Several researchers tackle the problem of sentiment analysis using machine learning algorithms.  ...  Machine Learning Approach for Sentiment Analysis There are three approaches in Machine Learning to analyze feelings and opinions, which are: supervised, unsupervised, and semi-supervised learning.  ... 
doi:10.22401/anjs.24.4.08 fatcat:hdjgfgh34bfn7faw2sva6wy74u

Android Apps Security Assessment using Sentiment Analysis Techniques: Comparative Study

Abeer Aljumah, Amjad Altuwijri, Thekra Alsuhaibani, Afef Selmi, Nada Alruhaily
2021 International Journal of Interactive Mobile Technologies  
Therefore, we pay attention to trying to spot insecurity apps, by analyzing user feedback on the Google Play platform and using sentiment analysis to determine the apps level of security.  ...  Yelp dataset (Hotel, Restaurant and Doctor). hotel reviews Stony brook university [8] [9] [10] [11] [6] [12] iJIM -Vol.15, No. 24, 2021 Table 3 . 3 Studies of aspect-based sentiment analysis No Dataset  ...  Sentiment analysis has many types, such as Fine-grained, Emotion detection, Aspect-based, and Multilingual sentiment analysis.  ... 
doi:10.3991/ijim.v15i24.27359 fatcat:aealokxf4jhh5dkkf3kb5kmely

Applying Machine Learning Improvements Derived From Diabetes Prediction To Macro Healthcare Systems

ROLAND BABAYEV, Colorado Technical University 4435 North Chestnut Street, Colorado Springs, CO 80907 USA
2020 Journal of Computer & Information Technology  
Machine learning based diabetes prediction research has leveraged feature reduction methods, ensemble machine learning models, hybrid combinations of supervised and unsupervised learning, 'white box' modelling  ...  For example, social network data analysis focused on uncovering public sentiment related to diabetes, physical activity, and food has been conducted 15 .  ...  Social Network and Questionnaire Based Improvements : Social network data can be used by EMRI in a manner similar to Ramsingh and Bhuvaneswari 15 in which diabetes sentiment analysis was applied to unstructured  ... 
doi:10.22147/jucit/110101 fatcat:finad4cdhfberhxw2uvtag46d4

Uncovering Flaming Events on News Media in Social Media

Praboda Rajapaksha, Reza Farahbakhsh, Noel Crespi, Bruno Defude
2019 2019 IEEE 38th International Performance Computing and Communications Conference (IPCCC)  
The labeled dataset is generated using an unsupervised model which is an improved unsupervised sentiment classification model.  ...  Comparing unsupervised true lable generation method with a baseline method VADAR lexicon and rule-based sentiment analysis tool [23] , which is widely used for classifying social media content, is considered  ... 
doi:10.1109/ipccc47392.2019.8958759 dblp:conf/ipccc/RajapakshaFCD19 fatcat:5ekmngw4effinnl3qeikkub7fy

Uncovering Flaming Events on News Media in Social Media [article]

Praboda Rajapaksha, Reza Farahbakhsh, Noel Crespi, Bruno Defude
2019 arXiv   pre-print
We use a deep Neural Network (NN) model that can identity sentiments of variable length sentences and classifies the sentiment of SNSs content (both comments and posts) to discover flaming events.  ...  Thus, our main objective of this study is to identify a way to detect flaming events in SNS using a sentiment prediction method.  ...  The labeled dataset is generated using an unsupervised model which is an improved unsupervised sentiment classification model.  ... 
arXiv:1909.07181v1 fatcat:lqfywr3twfhgjdpkktlcbzgxum

Extracting Aspects Hierarchies using Rhetorical Structure Theory [article]

Łukasz Augustyniak, Tomasz Kajdanowicz, Przemysław Kazienko
2019 arXiv   pre-print
We present an unsupervised technique using Rhetorical Structure Theory and graph analysis.  ...  The method could be easily extended with a sentiment analysis model and used to describe sentiment on different levels of aspect granularity.  ...  of Science and Higher Education fund for supporting internationally co-financed projects in 2016-2019 (agreement no. 3628/H2020/2016/2), and by the Faculty of Computer Science and Management, Wrocław University  ... 
arXiv:1909.01800v1 fatcat:n5pwtmghgrggbm2utt3r5ba7cy

Aspect-Level Sentiment Analysis Based on Bidirectional-GRU in SIoT

Waqar Ali, Yuwang Yang, Xiulin Qiu, Yaqi Ke, Yinyin Wang
2021 IEEE Access  
There are three sentiment analysis levels, also known as sentiment analysis: document level, sentence level, and aspect level.  ...  Supervised methods mostly based on classifiers such as CRFs and SVMs, and unsupervised methods based on words-toword dependencies or frequency analysis.  ... 
doi:10.1109/access.2021.3078114 fatcat:et5l33mxyrfs3etlzbahldxera

Systematic Review on Implicit and Explicit Aspect Extraction in Sentiment Analysis

Jaafar Zubairu Maitama, Norisma Idris, Asad Abdi, Liyana Shuib, Rosmadi Fauzi
2020 IEEE Access  
ACKNOWLEDGEMENT This research was financed by University Malaya Research University Grant IIRG003C-19SAH.  ...  It is an influential area of studies with very wide coverage, in the industrial domain, the term sentiment analysis has been used more frequently, but in academic settings, the terms sentiment analysis  ...  In view of this, [14] reviewed the state-of-theart studies that have used deep learning to address sentiment analysis problems, such as sentiment polarity.  ... 
doi:10.1109/access.2020.3031217 fatcat:vosmjncbe5h6lfaoucmjy2yxq4

Sentiment Analysis in the Era of Web 2.0: Applications, Implementation Tools and Approaches for the Novice Researcher

Mahmood Umar, Mansur Aliyu, Salisu Modi
2022 Caliphate Journal of Science and Technology  
Keywords: Sentiment Analysis; Web 2.0; Applications; Tools; Novice  ...  This study explores sentiment analysis of Web 2.0 for novice researchers to promote collaboration and suggest the best tools for sentiment data analysis and result efficiency.  ...  Acknowledgments The authors acknowledge the effort of Faculty of Science, Sokoto State University, particularly the Faculty Seminar Attendants for their input in this paper.  ... 
doi:10.4314/cajost.v4i1.1 fatcat:gijymvnbnfe7neht65ksyg2uoi

A Probabilistic Formulation of Unsupervised Text Style Transfer [article]

Junxian He, Xinyi Wang, Graham Neubig, Taylor Berg-Kirkpatrick
2020 arXiv   pre-print
Finally, we demonstrate the effectiveness of our method on a wide range of unsupervised style transfer tasks, including sentiment transfer, formality transfer, word decipherment, author imitation, and  ...  We present a deep generative model for unsupervised text style transfer that unifies previously proposed non-generative techniques.  ...  FURTHER ABLATIONS AND ANALYSIS Performance vs. Domain Divergence.  ... 
arXiv:2002.03912v3 fatcat:acatw2s37jalrfviz5tidtsq6m
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