Polarized User and Topic Tracking

This method provides an iterative classification of users and keywords in Digital traces of conversations in micro-blogging platforms and in OSNs. The method identifies polarize users for first, discovers then polarized keywords by monitoring the activities of previously classified users. This method allows to track users and topics over time. The algorithm is written in Python. Data are stored in MongoDB. Requirements: MongoDB and Pymongo.

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Accessibility Both
AccessibilityMode Download
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Availability On-Line
Basic rights Download
CreationDate 2016-03-14
Creator Cristina Muntean, cristina.muntean@isti.cnr.it
Dependencies on Other SW
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Field/Scope of use Any use
Github https://github.com/hpclab/PTR---Polarized-User-and-Topic-Tracking
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Item URL http://data.d4science.org/ctlg/ResourceCatalogue/polarized_user_and_topic_tracking
http://data.d4science.org/ctlg/ResourceCatalogue/polarized_user_and_topic_tracking
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Owner Cristina Muntean, cristina.muntean@isti.cnr.it
ProgrammingLanguage
RelatedPaper https://doi.org/10.1145/2911451.2914716
Requirement of non-disclosure (confidentiality mark)
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Sublicense rights No
Territory of use World Wide
ThematicCluster Text and Social Media Mining
UsageMode Download
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system:type SoBigData.eu: Method
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Author Muntean Cristina
Maintainer Muntean Cristina
Version 1
Last Updated 20 March 2018, 18:17 (CET)
Created 12 September 2016, 16:13 (CEST)