Detecting changes in context using time series analysis of social network

Researchers are getting great benefits of big data as information gathered from social media like Facebook, Twitter and being used to perceive the lot from family planning to predicting postpartum depression. Detecting behavioral changes in social networks represents an exciting new area of this pr...

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Main Authors: Nusratullah , Kajal, Shah , Asadullah, Ahmad Khan, Shoab, Haider Butt, Wasi
Format: Proceeding Paper
Language:English
Published: 2015
Subjects:
Online Access:http://irep.iium.edu.my/49209/2/kajal-paper-2015.pdf
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author Nusratullah , Kajal
Shah , Asadullah
Ahmad Khan, Shoab
Haider Butt, Wasi
author_facet Nusratullah , Kajal
Shah , Asadullah
Ahmad Khan, Shoab
Haider Butt, Wasi
author_sort Nusratullah , Kajal
collection IIUM
description Researchers are getting great benefits of big data as information gathered from social media like Facebook, Twitter and being used to perceive the lot from family planning to predicting postpartum depression. Detecting behavioral changes in social networks represents an exciting new area of this progression that is used to counter organizational behavior and terrorism. Such analysis in social networks in categorized as dynamic data analysis. To process data dynamically time series considers as an essential component. This research proposes a novel technique that uses time series analysis in cyber space based social networks to detect variances or changes in human context overtime.
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spelling oai:generic.eprints.org:492092016-05-24T03:24:31Z http://irep.iium.edu.my/49209/ Detecting changes in context using time series analysis of social network Nusratullah , Kajal Shah , Asadullah Ahmad Khan, Shoab Haider Butt, Wasi T10.5 Communication of technical information Researchers are getting great benefits of big data as information gathered from social media like Facebook, Twitter and being used to perceive the lot from family planning to predicting postpartum depression. Detecting behavioral changes in social networks represents an exciting new area of this progression that is used to counter organizational behavior and terrorism. Such analysis in social networks in categorized as dynamic data analysis. To process data dynamically time series considers as an essential component. This research proposes a novel technique that uses time series analysis in cyber space based social networks to detect variances or changes in human context overtime. 2015-11-02 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/49209/2/kajal-paper-2015.pdf Nusratullah , Kajal and Shah , Asadullah and Ahmad Khan, Shoab and Haider Butt, Wasi (2015) Detecting changes in context using time series analysis of social network. In: SAI Intellegence Systems Conference 2015, 10-11 November 2015, United Kingdom, London.
spellingShingle T10.5 Communication of technical information
Nusratullah , Kajal
Shah , Asadullah
Ahmad Khan, Shoab
Haider Butt, Wasi
Detecting changes in context using time series analysis of social network
title Detecting changes in context using time series analysis of social network
title_full Detecting changes in context using time series analysis of social network
title_fullStr Detecting changes in context using time series analysis of social network
title_full_unstemmed Detecting changes in context using time series analysis of social network
title_short Detecting changes in context using time series analysis of social network
title_sort detecting changes in context using time series analysis of social network
topic T10.5 Communication of technical information
url http://irep.iium.edu.my/49209/2/kajal-paper-2015.pdf
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AT ahmadkhanshoab detectingchangesincontextusingtimeseriesanalysisofsocialnetwork
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