Present study conducted a Natural Language Processing(NLP) on the titles, abstracts and whole paper of sample literature, together with keywords, to exact the high frequency words from all of above 4 units to identify the hot research issues via Pajek and Sci2. Moreover, present study performed Criterion-related Validity through correlation analysis and paired samples t-test by setting the hot research issues identified by whole paper as criterion and compared the correlation coefficient and t-value between whole papers and titles, abstracts and keywords to identify the Concurrency Validity of co-words analysis on hot research issues. The findings of this research include that: a) Those hot research issues identified by the abstract has a higher Concurrency Validity keywords. b) Aiming to identify the hot research issues, text is better than words from the perspective of Concurrency Validity, however, Validity is affected by the length of sampled text.