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A Proposal of Weight based Similarities Hybrid Algorithm on Social Media Posts through Crowdsourcing to Achieve High Performance Recommendation

by Fayza Amreen, Md. Golam Muktadir, Tonmoy Hossain, Nazmus Sakib
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International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 12 - Number 25
Year of Publication: 2019
Authors: Fayza Amreen, Md. Golam Muktadir, Tonmoy Hossain, Nazmus Sakib
10.5120/ijais2019451833

Fayza Amreen, Md. Golam Muktadir, Tonmoy Hossain, Nazmus Sakib . A Proposal of Weight based Similarities Hybrid Algorithm on Social Media Posts through Crowdsourcing to Achieve High Performance Recommendation. International Journal of Applied Information Systems. 12, 25 ( November 2019), 1-5. DOI=10.5120/ijais2019451833

@article{ 10.5120/ijais2019451833,
author = { Fayza Amreen, Md. Golam Muktadir, Tonmoy Hossain, Nazmus Sakib },
title = { A Proposal of Weight based Similarities Hybrid Algorithm on Social Media Posts through Crowdsourcing to Achieve High Performance Recommendation },
journal = { International Journal of Applied Information Systems },
issue_date = { November 2019 },
volume = { 12 },
number = { 25 },
month = { November },
year = { 2019 },
issn = { 2249-0868 },
pages = { 1-5 },
numpages = {9},
url = { https://www.ijais.org/archives/volume12/number25/1068-2019451833/ },
doi = { 10.5120/ijais2019451833 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-07-05T19:10:03.235132+05:30
%A Fayza Amreen
%A Md. Golam Muktadir
%A Tonmoy Hossain
%A Nazmus Sakib
%T A Proposal of Weight based Similarities Hybrid Algorithm on Social Media Posts through Crowdsourcing to Achieve High Performance Recommendation
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 12
%N 25
%P 1-5
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Recommendation based system on social media posts through crowd-sourcing is an ambitious task. This paper has formulated a hybrid algorithm acquaint with a new approach which is based on weight-based similarity to classify the social media posts as a positive or negative directional. In this paper, it has been proposed a scheme to use social media platforms taking crowd-source reactions and gathering information from the comments and posts by a user. The initial base post is generated by using the Raindrop algorithm where the credibility of the user account is factored as weight. The reaction from this base post can be used to determine whether the community is accepting the information of the base post or rejecting it with a negative impression. To find positively relevant comments and posts regarding the base post, the MinHash algorithm is used. Firstly, using substantial steps of Natural Language Processing (NLP) for pre-processing the data. Then the generalized MinHash algorithm is used to extract the relevant data from all the comments and the posts with the signature. Finally, Longest Common Subsequence (LCS) Algorithm is implemented to categorize the supporting most similar data, thus the post that triggered by the user will get the directional data from the relatively matched comments from the shingles.

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Index Terms

Computer Science
Information Sciences

Keywords

Crowdsourcing Data Mining Natural Language Processing (NLP) MinHash Confusion Matrix Raindrop Longest Common Subsequence (LCS) Algorithm

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