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

fYear

2012

fDate

16-18 Nov. 2012

Firstpage

308

Lastpage

313

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Technologies and Applications of Artificial Intelligence (TAAI), 2012 Conference on

Conference_Location

Tainan

Print_ISBN

978-1-4673-4976-5

Type

conf

DOI

10.1109/TAAI.2012.56

Filename

6395046