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Progress in Deep Learning Mechanisms for Information Extraction from Social Networks: An Expository Overview

by Israel Fianyi, Gifty Andoh Appiah
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 174 - Number 24
Year of Publication: 2021
Authors: Israel Fianyi, Gifty Andoh Appiah
10.5120/ijca2021921155

Israel Fianyi, Gifty Andoh Appiah . Progress in Deep Learning Mechanisms for Information Extraction from Social Networks: An Expository Overview. International Journal of Computer Applications. 174, 24 ( Mar 2021), 50-63. DOI=10.5120/ijca2021921155

@article{ 10.5120/ijca2021921155,
author = { Israel Fianyi, Gifty Andoh Appiah },
title = { Progress in Deep Learning Mechanisms for Information Extraction from Social Networks: An Expository Overview },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2021 },
volume = { 174 },
number = { 24 },
month = { Mar },
year = { 2021 },
issn = { 0975-8887 },
pages = { 50-63 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume174/number24/31826-2021921155/ },
doi = { 10.5120/ijca2021921155 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:23:01.762418+05:30
%A Israel Fianyi
%A Gifty Andoh Appiah
%T Progress in Deep Learning Mechanisms for Information Extraction from Social Networks: An Expository Overview
%J International Journal of Computer Applications
%@ 0975-8887
%V 174
%N 24
%P 50-63
%D 2021
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Deep learning algorithms have shown to be robust in extracting high quality information from a wide range of online platforms. Incidentally, social networks and other related online platforms are known to hold a copious amount of unstructured user-generated content. To date, machine learning and deep learning approaches for mining textual data have received so much attention from researchers and industry players Deep learning is good at independently learning from complex feature representation and make intelligent decisions from data. However, with the influx if different deep learning methods for information extraction, understanding and finding the current challenges and recent advances in these algorithms is daunting. This paper investigates existing pieces of literature to appreciate the trajectory of deep learning for information extraction in Natural Language Understanding. The study further considers the state-of-the-art, open challenges, as well as the tools and methodologies involved in undertaking information extraction tasks from Unstructured data. The study considers relevant published articles from the year 2009-2020 that focused on deep learning approach for information extraction from text. The investigations of this paper provide extensive clarity to the research field of Natural Language Processing with deep learning. It identifies current research problems, recommends directions for future research. The paper is designed to help non-expert researchers comprehend the fundamentals of deep learning and Natural Language Processing methods for Information Extraction.

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Index Terms

Computer Science
Information Sciences

Keywords

Deep learning Algorithms Natural Language Processing Information Extraction Social Networks

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