Authorship Attribution for Social Media Forensics
Authorship Attribution for Social Media Forensics project report on web mining The veil of anonymity provided by smartphones with pre-paid SIM cards, public Wi-Fi hotspots, and distributed networks like Tor has drastically complicated the task of iden-tifying users of social media during forensic investigations. In some cases, the text of a single posted message will be the only clue to an author’s identity.
All authors possess peculiarities of habit that influence the form and content of their written works. These characteristics can often be quantified and measured using machine learning algorithms. In this Authorship Attribution for Social Media Forensics project report article, we provide a comprehensive review of the methods of authorship attribution that can be applied to the problem of social media forensics.
Authorship Attribution for Social Media Forensics Project report on web mining We have investigated the learning of authorship categories for the case of both aggregated and multi-topic e-mail documents. We used an extended set of predominantly contentfree e-mail document features such as structural characteristics and linguistic patterns. The classifier used was the Support Vector Machine learning algorithm. Authorship Attribution for Social Media Forensics project on web mining Experiments on a number of e-mail documents generated by different authors on a set of topics gave encouraging results for both aggregated and multi-topic author categorisation.
|Project Name||Authorship Attribution for Social Media Forensics|
|Project Category||Web mining and Security|
|Project Cost||65 $/ Rs 4999|
|Delivery Time||48 Hour|
|For Support||WhatsApp: +91 9481545735 or Email: email@example.com|
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