  The prevalence of different kinds of electronic devices and the volume of
content on the Web have increased the amount of plagiarism, which is considered
an unethical act. If we want to be efficient in the detection and prevention of
these acts, we have to improve today's methods of discovering plagiarism. The
paper presents a research study where a framework for the improved detection of
plagiarism is proposed. The framework focuses on the integration of social
network information, information from the Web, and an advanced semantically
enriched visualization of information about authors and documents that enables
the exploration of obtained data by seeking of advanced patterns of plagiarism.
To support the proposed framework, a special software tool was also developed.
The statistical evaluation confirmed that the employment of social network
analysis and advanced visualization techniques led to improvements in the
confirmation and investigation stages of the plagiarism detection process,
thereby enhancing the overall efficiency of the plagiarism detection process.
