A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Filters
Entity Extraction from Social Media using Machine Learning Approaches
2015
Forum for Information Retrieval Evaluation
Preserved Fulltext
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)
2015
Forum for Information Retrieval Evaluation
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
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]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
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)
2015
Forum for Information Retrieval Evaluation
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
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
2016
Procedia Computer Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
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
2015
Journal of Biomedical Informatics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
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
2022
Vaccines
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
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"
2019
Information
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
, 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
2021
International Journal of Advanced Computer Science and Applications
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
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
2020
IEEE Access
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
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]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
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)
2018
AAAI Conference on Human Computation & Crowdsourcing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
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
2022
International Journal for Research in Applied Science and Engineering Technology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
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
2019
AMBIENT SCIENCE
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
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]
2018
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
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
« Previous
Showing results 1 — 15 out of 41,974 results