From Citation count to Argumentation count: a new metric to indicate the usefulness of an article

Citation count is a quantifiable measure to indicate the number of times an article is cited by other articles. It is believed that if an article is cited often then it must be an important or influential article; however, there is no guarantee that the most cited articles are good in quality. In this paper, the author suggests “argumentation count”, a new metric for citation analysis. The proposed metric, argumentation count is a triplet of quantities for each concept of an article that helps in providing a quantifiable measure about the usefulness of an article. Introduction Since many years, most of the publication house, academic search engines and academia are using citation count as a quantifiable measure to indicate the impact or usefulness of an article. A citation count is the number of times an article is cited by other articles. It is usually considered to indicate the quality of the article. If an article is cited often it must be an important or influential article. It is widely used as a benchmarking tool to rank the articles or journals (David 2002). Citation analysis or bibliometrics is a field of study that deals with the importance and usage of articles, journals and author profiles. Citation count is a quantifiable metric that can be applied to an article, journal or an author. Citation count can be applied to:  an individual article to signify how often it was cited  an author to signify the total citations, or average citation count per article  a journal to signify average citation count for the articles in the journal In recent days, new metrics and tools are gaining importance that is based on citation count. The h-index tries to categorize output of a researcher (Hirsh 2005). Improved metrics are being proposed over the earlier ones for instance g-index was proposed over h-index (Leo 2006), however, most of the metrics are based on the idea of citation count. Most of the academic search engines are providing citation count along with the search results. It is assumed that the citation count is always less than the actual count as the search engines may not be able to consider each article that has cited the work. A more serious issue is that the citation count cannot identify the authenticity of the article in terms of quality and usefulness. It is always assumed that an article is of importance if it is highly cited. Few researchers try to take advantage of citation analysis by using selfcitation to manipulate the citation count. With the development of information retrieval technologies (Manning and Raghvan 2010), a new term called “argumentation mining” is being conceptualized that can be reasonably used to identify the importance of an article. The subsequent section of this paper explores the term argumentation mining and advocates its use as a metric for bibliometrics.