[Python] Distinguish between references and citations with Scrappy and scholar.py

Dear experts :) In python, we need an implementation which will discriminate between references and citations ( or heterogenous references). Heterogeneous references to one's work are references to one's work within the work of others. The word gives the English "citation" and is the opposite of self-reference (which means that in your paper you refer to your older paper). Each report has at least one or more authors. Several references cite other older ones on which they relied for authorship. Suppose there is a new report, and if its author is the same as that of the reported reference he uses, then we have the case of self-reference. But if he is not the same but just another author who is referenced, then we have a case of heterogenous reference or citation. We can use machine learning as long as we have good results to this. You can use Scrapy and [login to view URL] ( [login to view URL] ) I can send you a workaround which may be of help (its translation is bad but I can explain it) The budget is $50 just for the code, and the deadline is 1-2 weeks. After this we may need a documentation. After the documentation we may need a relevant research report. Thank you a lot in advance