# Identifying Mis-Configured Author Profiles on Google Scholar Using Deep Learning
## 7 Application Case Study
### Case Study 1: Outstanding Scholar Searching  
Google Scholar provides the service that users can search for scholars according to their research fields. The searching results are sorted by each scholar's total number of citations and listed by 10 scholars per page. Since users tend to view the first several pages, the reliability of author profiles with relatively high numbers of citations is much more important. We treat the scholars on the first 10 pages, namely the top 100 scholars of each research field, as the outstanding scholars. In this part, we pay attention to these outstanding scholars and analyze the mis-configuration of their author profiles. We choose the 10 research fields with the largest numbers of authors in our dataset for analysis, which is listed in Table 6. The top 100 scholars of these 10 research fields who are listed in the first 10 pages are observed. We count the mis-configured author profiles of these 100 scholars. As shown in Figure 3, each of the 10 fields has more than 15 author profiles to be mis-configured. In particular, there are 3 fields with over half of the author profiles being mis-configured. Since the first searching result page is the most important page and most frequently viewed, we also display the number of mis-configured author profiles on the first page in Figure 3 and the numbers of mis-configured ones are excessively large. We believe that a scholar who has a large number of citations tends to have lots of papers in her paper list, therefore is more likely to include others' papers by mistakes. Interestingly, the number of mis-configured author profiles belonging to scholars that list natural language processing (NLP) or data science in their research fields are smaller than that of other eight fields. Intuitively, it is less common for research in NLP to combine with other fields, so the possibility of including others' papers is small. Researches in some other fields such as data mining are similar to those in data science. The reason for such a small number of mis-configured author profiles is that maybe the term is much more professional and the scholars who tend to include this term in their research field lists are more rigorous. Due to the critical impact of the outstanding scholars, we conduct a comprehensive analysis on the mis-configuration of these scholars' author profiles. Due to the overlapping of scholars in different fields, there are totally 865 outstanding scholars in the first ten pages of these ten research fields. Of them, 341 have mis-configured author profiles. First, we observe the academic age distribution of these scholars. We can estimate the academic age of a scholar by observing the largest time interval between two papers in her paper list. If the time interval is larger than 40 years, we regard her as a relatively senior scholar. Of these scholars, 46.9 percent are senior. Among the senior scholars' author profiles, 70.4 percent are mis-configured and 83.9 percent of mis-configured author profiles belong to the senior scholars, which indicates that scholars might not actively manage their author profiles after retirement. Then, we study the country distribution of these outstanding scholars. Utilizing the institutional email addresses shown on the author profiles, we can also detect \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Methods** & **Precision** & **Recall** & **F1-Score** \\ \hline Model w/o Social & 0.9657 & 0.6817 & 0.7992 \\ Model w/o Manual & 0.9438 & 0.7764 & 0.8520 \\ Our Proposed Model & 0.9508 & 0.8513 & 0.8983 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Performance of the ablation study. which country each scholar works in. We extract the email domain from the email address and then we query domain name servers (DNS) to obtain its corresponding IP address. GeoLite2 database [37] is used to translate IP address to country information. The country distribution of these outstanding scholars is shown in Figure 4a.