Title :
Hidden Trends in 90 Years of Harvard Business Review
Author :
Chia-Chi Tsai ; Chao-Lin Liu ; Wei-Jie Huang ; Man-Kwan Shan
Author_Institution :
Dept. of Comput. Sci., Nat. Chengchi Univ., Taipei, Taiwan
Abstract :
In this paper, we demonstrate and discuss results of our mining the abstracts of the publications in Harvard Business Review between 1922 and 2012. Techniques for computing n-grams, collocations, basic sentiment analysis, and named-entity recognition were employed to uncover trends hidden in the abstracts. We present findings about international relationships, sentiment in HBR´s abstracts, important international companies, influential technological inventions, renown researchers in management theories, US presidents via chronological analyses.
Keywords :
abstracting; data mining; humanities; natural language processing; reviews; text analysis; HBR abstract sentiment; Harvard Business Review; US presidents; basic sentiment analysis; chronological analyses; hidden trends; international companies; international relationships; management theories; n-gram computing techniques; named-entity recognition; publication abstract mining; technological inventions; Abstracts; Companies; Dictionaries; Economic indicators; Market research; USA Councils; collocation; economic trends; sentiment analysis; temporal analysis; text mining;
Conference_Titel :
Technologies and Applications of Artificial Intelligence (TAAI), 2012 Conference on
Conference_Location :
Tainan
Print_ISBN :
978-1-4673-4976-5
DOI :
10.1109/TAAI.2012.56
