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Anomaly Detection In Practice Using Python

Shirishkumar Bari1 , Abhijit Patankar2

Section:Survey Paper, Product Type: Journal Paper
Volume-7 , Issue-7 , Page no. 241-246, Jul-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i7.241246

Online published on Jul 31, 2019

Copyright © Shirishkumar Bari, Abhijit Patankar . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Shirishkumar Bari, Abhijit Patankar, “Anomaly Detection In Practice Using Python,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.7, pp.241-246, 2019.

MLA Style Citation: Shirishkumar Bari, Abhijit Patankar "Anomaly Detection In Practice Using Python." International Journal of Computer Sciences and Engineering 7.7 (2019): 241-246.

APA Style Citation: Shirishkumar Bari, Abhijit Patankar, (2019). Anomaly Detection In Practice Using Python. International Journal of Computer Sciences and Engineering, 7(7), 241-246.

BibTex Style Citation:
@article{Bari_2019,
author = {Shirishkumar Bari, Abhijit Patankar},
title = {Anomaly Detection In Practice Using Python},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {7 2019},
volume = {7},
Issue = {7},
month = {7},
year = {2019},
issn = {2347-2693},
pages = {241-246},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4752},
doi = {https://doi.org/10.26438/ijcse/v7i7.241246}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i7.241246}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4752
TI - Anomaly Detection In Practice Using Python
T2 - International Journal of Computer Sciences and Engineering
AU - Shirishkumar Bari, Abhijit Patankar
PY - 2019
DA - 2019/07/31
PB - IJCSE, Indore, INDIA
SP - 241-246
IS - 7
VL - 7
SN - 2347-2693
ER -

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Abstract

On 8th August 2018, Kerala had a very heavy rainfall, resulting filling of dams caused flood situation in Kerala. Many people started posting twits about this and people living in that area were alerted. Administration department started their rescue operations. Here social media played key role in locating people and providing help to them. A lot of campaigns were started to collect financial aid to the affected people. Here we again felt power of social media that can positively impact the society. Twitter, a popular micro blogging service, has received much attention recently. An important characteristic of Twitter is its real-time nature. It is also extremely popular because the information gets spread more widely and rapidly. It’s important to detect anomalous events which are trending on the social media and be able to monitor their evolution and find related events. This paper talks about how to detect the anomalies in tweets.

Key-Words / Index Term

Anomaly, Types of Anomalies, Machine Learning, Text Stream, Twitter Data, Social media analysis

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