Abstract:
Crowdsourcing refers as a practice of engaging a group of people for a common goal powered
by enhanced technologies and social media. As millions of events happens every second of
day, it’s not possible for journalists to cover all of them. In context of Journalism,
crowdsourcing, nowadays, provide a platform for general public to act and communicate thus
improving their coverage.
Cybercrime is defined as aggressive, intentional act performed through electronic
communications. In recent years, there is intense increase in racism, sexism and other types of
aggressive cyber threats. As Pakistan is in list of fastest growing Internet-using countries,
ultimately increasing the need to tackle cybercrimes. Confronting cybercrimes therefore
requires development of robust detection method in unsupervised manner.
The focus of this research is to propose a model for detection of cyber offences in Pakistan
reported through news articles and blogs. The first step is to compile existing cybercrime
detection methods and perform comparative analysis of methods along with their weaknesses.
Comparative analysis will assist in proposing a model for cybercrimes detection through
electronic media. Further, in order to analyze authenticity of these news attained via news
articles/blogs, source verification process is performed on acquired data by selecting various
authenticity parameters and assigning weightages to these parameters.
