Academic social networks have emerged as an integral part of today’s scholarly societies, being a key resource that facilitates scientific ranking involving authors, publications, and venues (journals, conferences and workshops). Such rankings play an essential role in today’s Scientometrics. In this research, we study and inspect the methods for ranking of academic entities that constitute an academic social network. Ranking of authors is becoming a challenging task with continuous growth in size of computationally analyzable data and dynamic nature of scholarly networks. Ranking of authors is important for academic recommendations tasks like faculty recruitment and promotion, selection of research grants awards, selection of researchers for collaborative research and for review of scientific work. In today’s trans-discipline oriented academic networks, researchers work in collaboration with each other and hence, influence the work and ranking of each other. We understand that, contemplating the impact of an author’s own work along with the influence of his or her collaborators give a complete picture of the standing of an author. Hence, it is not only the author’s own productivity and quality of work that needs to be considered while ranking an authors, the influence of his co-workers needs to be addressed as well. This research ranks authors not only on the basis of their own work but, also quantifies the impact of mutual influence of authors when they work in collaboration, along with exclusivity in their received citations. The work of authors is influenced by the work of their co-authors, more so if coauthors are seniors. Tracking the citations revived by an author is also an important factor to measure the impact of an author. This study proposes Mutual Influence and Citation Exclusivity Author Rank method for finding the mutual influence based positioning of authors along with the analysis of received citations. Thus, we have highlighted the effect of collaboration and the empirical results, when compared with results of baseline methods, show that the proposed method retrieves satisfactory results. These results are applicable in academic recommendation tasks. When it comes to collaboration, if it is with a well-known scientist of a particular field, it can lead a researcher to become a “rising stars”. Rising stars are the researchers who currently have a low profile, but have the ability to become an expert in future. In many nature science domains, while collaboration is inevitably becoming a vital factor for success, cultivation of new promising researchers is becoming a by-product of this process. Young researchers or doctorate candidates can grow up quickly by tutor''s instructions, advanced experimental environment, and fierce competition among themselves. In this research, we study the hypothesis: Does standing on shoulders of a giant can lead you to success? The results show that researchers who are lucky enough to work with a well-known scientist of a field are more productive, collaborative and become influential very soon. The results exhibit a great deal of promise and highly comply with our hypothesis to support and strengthen it. We anticipate that ranking of academic entities within context of topics will grow in importance, as trans-disciplinary collaboration continues to become a norm in scholarly practice. Topic based ranking of authors, papers and journals can serve as a vital tool for identifying authorities of a given topic within a particular domain. Most of the current methods are based on parameters like publication count, citations count and are topic independent, hence ignore the intra-field differences. We introduce a novel method, Domain Specific Indexing, for domain based indexing of authors to measure researcher’s productivity in a given topic. DSI calculates the standing of an author in all topics of his or her interest by considering topic based citations instead of using overall citations like traditional methods. Secondly, we adopted the Similarity measure and Kandal’ Tau for evaluation and comparison of Ad hoc h-index and Domain based Indexing of authors. Results show a great deal of promise for the proposed method. Existing methods that measure topic based scholarly output are limited to homogeneous networks. This study proposes a new informative metric called Topic-based Heterogeneous Rank (TH Rank) which measures the impact of a scholarly entity with respect to a given topic in a heterogeneous scholarly network which contains authors, papers and journals. Results show that TH Rank can effectively identify the most prestigious authors, papers and journals related to a specific topic.