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Rumor source identification in social networks is an emerging topic, introduced by Ref. [9]. In order to find the rumor source in network, first task is to classify given data rumor or not, then apply source detection techniques on network which contain nodes that are infected by rumors. The following Figure 1.13 will give idea about how a rumor is classified from given data using classification algorithms and how rumor sources are classified based on metrics. Initially, it is needed to collect dataset of sender and receiver messages (rumor) from social network, do data processing like removing urls, hashttags, stopwords, etc. and annotation. Next construct propagation graph finds rumor or misinformation, and selects any suitable diffusion model to get information about how a rumor is diffused in network, suitable metrics for source detection and evaluation. It also classifies sources based on metrics available, do validation and analysis of results.

Source detection approaches are classified into two most important categories: single source detection and multiple source detection [10].

Figure 1.13 Rumor source detection process.