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Entity Extraction from Social Media using Machine Learning Approaches

Sombuddha Choudhury, Somnath Banerjee, Sudip Kumar Naskar, Paolo Rosso, Sivaji Bandyopadhyay
2015 Forum for Information Retrieval Evaluation  
In this work, we describe an automatic entity extraction system for social media content in English as part of our participation in the shared task on Entity Extraction from Social Media Text in Indian  ...  Our method uses simple features such as window of words, capitalization, dictionary word, part of speech tags, hashtag, etc.  ...  CONCLUSIONS In this paper, we have presented a brief overview of our machine learning based systems to address the automatic NE identification problem on social media.  ... 
dblp:conf/fire/ChoudhuryBNRB15 fatcat:5cmsetf7qvfapc3kawbcj7jtx4

Entity Extraction from Social Media Text Indian Languages (ESM-IL)

Chintak Mandalia, Memon Mohammed Rahil, Manthan Raval, Sandip Modha
2015 Forum for Information Retrieval Evaluation  
The paper shows working methodology and its result on named entity extraction from social media text of fire 2015.  ...  NER in Hindi by aggregating approaches such as Rule based CRF suite and for tagging RDRpostagger and geniatagger.  ...  This work is part of ESM-IL (Entity Extraction from Social Media Text -Indian Language).  ... 
dblp:conf/fire/MandaliaRRM15 fatcat:kggo5dlbyffujodzrs5onz2ojm

A Machine Learning Pipeline to Examine Political Bias with Congressional Speeches [article]

Prasad hajare, Sadia Kamal, Siddharth Krishnan, Arunkumar Bagavathi
2021 arXiv   pre-print
Political bias in social media has been studied in multiple viewpoints like media bias, political ideology, echo chambers, and controversies using machine learning pipelines.  ...  We also present a machine learning approach that combines features from cascades and text to forecast cascade's political bias with an accuracy of about 85%.  ...  Political bias detection from the given text using machine learning approaches has been a growing interest among researchers.  ... 
arXiv:2109.09014v1 fatcat:e6vwafinfrel7ellyygla7qfr4

Vira@FIRE 2015: Entity Extraction from Social Media Text Indian Languages (ESM-IL)

Vira Bagiya, Anjana Patel, Amit Ganatra
2015 Forum for Information Retrieval Evaluation  
In this paper we have tried to identify and extract "Named Entities" from social media text using conditional random field-(CRF) [3] .  ...  The paper represents our working methodology and result on Entity Extraction from Social Media Text Indian Languages task of FIRE-2015.  ...  Task Description "Entity extraction from social media text in Indian Languages" is a task in which we have provided different tweets.  ... 
dblp:conf/fire/BagiyaPG15 fatcat:s3zpqmxamzgqbej6olfuvc3n7q

A Hybrid Approach for Drug Abuse Events Extraction from Twitter

Ferdaous Jenhani, Mohamed Salah Gouider, Lamjed Ben Said
2016 Procedia Computer Science  
Many approaches, ranging from linguistic techniques to learning algorithms, were proposed to succeed this task.  ...  Since their emergence, social media have become a reliable source of social events which attracted the interest of research community to extract them for many business requirements.  ...  Despite its novelty, event extraction from social media gave birth to three approaches; rule-based, learning-based and hybrid approaches.  ... 
doi:10.1016/j.procs.2016.08.121 fatcat:ekte7dpdpjg6zornkbqav3e6ma

A research framework for pharmacovigilance in health social media: Identification and evaluation of patient adverse drug event reports

Xiao Liu, Hsinchun Chen
2015 Journal of Biomedical Informatics  
However, extracting patient adverse drug event reports from social media continues to be an important challenge for health informatics research.  ...  The framework consists of medical entity extraction for recognizing patient discussions of drug and events, adverse drug event extraction with shortest dependency path kernel based statistical learning  ...  Chanadda Chinthammit for their advices from clinical and pharmaceutical perspectives in this study. We thank Jing Liu for her analytical work on the MedHelp forum.  ... 
doi:10.1016/j.jbi.2015.10.011 pmid:26518315 fatcat:53nu3jrxfbdmxe2yqpaaqyrija

Using a Machine Learning Approach to Monitor COVID-19 Vaccine Adverse Events (VAE) from Twitter Data

Andrew T. Lian, Jingcheng Du, Lu Tang
2022 Vaccines  
The goal of this project is to develop a machine learning and natural language processing approach to identify COVID-19 vaccine adverse events (VAE) from Twitter data.  ...  Social media can be used to monitor the adverse effects of vaccines.  ...  Acknowledgments: The authors thank Jingqi Wang for the guidance on using CLAMP software, as well as mapping adverse event entities to MedDRA PT terms.  ... 
doi:10.3390/vaccines10010103 pmid:35062764 pmcid:PMC8781534 fatcat:fwszstfmercwhkyb43itslahga

Editorial for the Special Issue on "Natural Language Processing and Text Mining"

Pablo Gamallo, Marcos Garcia
2019 Information  
, especially Web content and social media.  ...  The paper "An Improved Word Representation for Deep Learning Based NER in Indian Languages" [9] describes a named entity recognition system based on deep learning approaches for Indian languages.  ... 
doi:10.3390/info10090279 fatcat:mqgmakagw5gjthh2dcztn72b4e

Multistage Sentiment Classification Model using Malaysia Political Ontology

Nur Farhana Ismail, Nur Atiqah Sia Abdullah, Zainura Idrus
2021 International Journal of Advanced Computer Science and Applications  
Now-a-days, people use social media platforms such as Facebook, Twitter, and Instagram to share their opinions on particular entities or services.  ...  Then the extracted features are tested using different classifiers. As a result, Linear Support Vector Machine yields an accuracy of 86.4% for the classification.  ...  This study receives funding from the Ministry of High Education (MOHE)  ... 
doi:10.14569/ijacsa.2021.0121048 fatcat:fmgxrfje6bhxxocxrlm7y22bme

A Hybrid Machine Learning Pipeline for Automated Mapping of Events and Locations from Social Media in Disasters

Chao Fan, Fangsheng Wu, Ali Mostafavi
2020 IEEE Access  
INDEX TERMS Machine learning pipeline, social media, disasters, automated mapping.  ...  Existing studies have employed machine learning methods to conduct coarse-grained event detection and analyze the geographical location information from geotagged social media data.  ...  THE HYBRID MACHINE LEARNING PIPELINE We propose a hybrid machine learning pipeline to detect the evolution and geographical distribution of disaster events using social media data (see Figure 1 ).  ... 
doi:10.1109/access.2020.2965550 fatcat:4lwgebyimjbyhguia43fisikqe

Event Extraction Based on Deep Learning in Food Hazard Arabic Texts [article]

Fouzi Harrag, Selmene Gueliani
2020 arXiv   pre-print
We proposed here a model based on deep recurrent networks to extract the events from social media feeds.  ...  Event extraction on the other hand indicates an understanding of events across social media posts streams.  ...  Common machine learning architecture for NER Constructing a named entity recognition solution using a machine learning approach requires many computational steps including preprocessing, learning, classification  ... 
arXiv:2008.05014v1 fatcat:ghtuhrp2cvdnlcl3bukyihea44

A Human in the Loop Approach to Capture Bias and Support Media Scientists in News Video Analysis (short paper)

Panagiotis Mavridis, Markus de Jong, Lora Aroyo, Alessandro Bozzon, Jesse de Vos, Johan Oomen, Antoaneta Dimitrova, Alec Badenoch
2018 AAAI Conference on Human Computation & Crowdsourcing  
In this paper we advocate the need for accurate methods for bias identification in video news item, to enable rich analytics capabilities in order to assist humanities media scholars and social political  ...  We propose to analyze biases that are typical in video news (including framing, gender and racial biases) by means of a human-in-the-loop approach that combines text and image analysis with human computation  ...  by the Capture Bias project 9 , part of the VWData Research Programme funded by the Startimpuls programme of the Dutch National Research Agenda, route "Value Creation through Responsible Access to and use  ... 
dblp:conf/hcomp/MavridisJABVODB18 fatcat:3estl4ahxbfftakvfd5j3dphaa

Named Entity Recognition in Social Media Data

Archisha Sharma, Shruti Shreya, Shrishail Terni
2022 International Journal for Research in Applied Science and Engineering Technology  
The fields in which Named Entity Recognition is used for analysis of data provided from various social media sites, include rumour detection, controversy detection, sentiment analysis, medical field (such  ...  Through this paper, different methods proposed for the purpose of social media data extraction using Named Entity Recognition, have been studied in detail and a comparison has been provided for the same  ...  Machine learning algorithms are used to solve sentiment analysis from social media networks, which is a fairly old issue.  ... 
doi:10.22214/ijraset.2022.46181 fatcat:7t2mmuqgqzawpemwz5zl2u7wie

A Perspective on Text Classification, Clustering, and Named-entity Recognition in Social Media

Kia Jahanbin, Research Center for Social Determinants of Health, Jahrom Universityof Medical Sciences, Jahrom, Iran, Fereshte Rahmanian, Vahid Rahmanian, Masihollah Shakeri, Heshmatollah Shakeri, Zhila Rahmanian, Abdolreza Sotoodeh Jahromi
2019 AMBIENT SCIENCE  
Mukkamala . (2014) and Nguyen . (2015) use interchangeably the terms Big Social Data and Social Big Data to refer the overall data created by social media.  ...  After the emergence of social media, an enormous amount of data started to generate.  ...  Using these two resources, annotations are automatically achieved to train machine learning approaches. The technique was evaluated on the NER shared-task datasets of i2b22010 and SemEval 2014.  ... 
doi:10.21276/ambi.2019.06.1.ga01 fatcat:mvug2ixu5fe3jfshswi42lxofa

Enhancing Decision Making Capacity in Tourism Domain Using Social Media Analytics [article]

Supun Abeysinghe, Isura Manchanayake, Chamod Samarajeewa, Prabod Rathnayaka, Malaka J. Walpola, Rashmika Nawaratne, Tharindu Bandaragoda, Damminda Alahakoon
2018 arXiv   pre-print
Hence, we propose a social media analytics platform which has the capability to identify discussion pathways and aspects with their corresponding sentiment and deeper emotions using machine learning techniques  ...  Social media has gained an immense popularity over the last decade. People tend to express opinions about their daily encounters on social media freely.  ...  Index Terms-social media, tourism, insights, machine learning I. INTRODUCTION Nowadays social media plays a key role in lives of people in the world.  ... 
arXiv:1812.08330v1 fatcat:klb4vewpfjdd3lfvzzla5nes4i
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