Nowadays there is a growing interest on university rankings. Many works can be found related to this topic in the literature review. QS and THE (Times Higher Education) are two of the most important university ranking systems in the World. In these ranking systems, the number of the universities in Turkey has been gradually increasing. It is known that these ranking systems use different kinds of criteria in order to evaluate universities all over the world. One of their criteria is number of publications indexed in citation databases such as Web of Science and Scopus. QS retrieves data via Scopus. As it is known Scopus is almost twice as wide as Web of Science in terms of coverage. THE was retrieving data via Web of Science until 2015 but it also has started to retrieve data via Scopus as of 2015. When examined comparisons between these two citation databases in 2010-2014 for Sabanci University, it has been decided to use content analysis method very deeply about the situation of publications in WoS but not in Scopus. In this context, firstly it has been looked for the publications which can not be found when it is searched as “Sabanci University” in Affliation search criteria. The reasons are inaccurate, incomplete, adjacent and other entries such as “Sabanc University”, “Sabanici University”, “SabanciUniversity”, “Sabancy University” and so on. Even the name Sabanci University is typed wrong, all wrong entries could not collect under one roof with a right name in order not to be used in the mapping system in Scopus. In addition, there are also problems in terms of wrong year entries. For instance even though publication year is 2014, it appears in 2015 when sorted the results by year. Never has it been so complex to retrieve data from a database. When analyzed most of the problematic records, there has appeared some funny wrong entries. Turkish character “ı” has appeared as “dotless” as has been entered as “sabancdotless”. In this study, such problem cases will be dealt with one by one. It is possible to predict there can be many more mistakes when a university’s title has more than one word. In countries where English is not the official language, there may be two entries for universities in both their own language and in English. When acronyms are added the problem grows. For instance, Middle East Technical University (Ortadoğu Teknik Üniversitesi), and for its acronyms we could cite: ODTÜ; METU. Another issue concerning names in countries where English is not the official/ first language is the letters in the name of the university which do not exist in English as mentioned above, the letter “ı” in Sabancı. It is predicted that there may be a lot of institutions faced with this problem which Sabanci University has. Thus, data retrieval which affects ranking so profoundly should be analysed in the scope of data mining in their own entries sensitively so that institutions could get the ranking they deserve.