Linguistic sleuthing for innovators
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Linguistic sleuthing for innovators Francesca Greco1 · Ken Riopelle2 · Francesca Grippa3 · Andrea Fronzetti Colladon4 · Julia Gluesing2 Accepted: 29 August 2020 © The Author(s) 2020
Abstract For centuries “innovation” has been a topic of book authors and academic researchers as documented by Ngram and Google Scholar search results. In contrast, “innovators” have had substantially less attention in both the popular domain and the academic domain. The purpose of this paper is to introduce a text analysis research methodology to linguistically identify “innovators” and “non-innovators” using Hebert F. Crovitz’s 42 relational words. Specifically, we demonstrate how to combine the use of two complementary text analysis software programs: Linguistic Inquiry and Word Count and WORDij to simply count the percent of use of these relational words and determine the statistical difference in use between “innovators” and “noninnovators.” We call this the “Crovitz Innovator Identification Method” in honor of Herbert F. Crovitz, who envisioned the possibility of using a small group of 42 words to signal “innovation” language. The Crovitz Innovator Identification Method is inexpensive, fast, scalable, and ready to be applied by others using this example as their guide. Nevertheless, this method does not confirm the viability of any innovation being created, used or implemented; it simply detects how a person’s language signals innovative thinking. We invite other scholars to join us in this linguistic sleuthing for innovators. Keywords Text mining methods · Innovation · Innovators · Computational linguistics · Language use · Natural language processing (NLP)
1 Introduction For centuries, “innovation” has been a topic of book authors and academic researchers as documented by Google Books Ngram and Google Scholar search results. In contrast, “innovators” have had substantially less attention. Figure 1 is the Google Books Ngram search results for the terms: “innovation” and “innovators” from 1800 to 2008, which is the most recent date for which data are available.1 A visual inspection of the graph makes it obvious that authors 1
Google Ngram Book search last accessed on April 5, 2020. https://books.google.com/ngrams/graph?content=innovation%2Cinnovators%2C&year_start=1800&year_ end=2008&corpu s =15&smoot h ing=3&share = &direc t _url=t1%3B%2Cinn ovati o n%3B%2Cc0%3B. t1%3B%2Cinn o vato r s%3B%2Cc0#t1%3B%2Cinn o vati o n%3B%2Cc0%3B.t1%3B%2Cinn o vato rs%3B%2Cc0 * Francesca Greco [email protected] Extended author information available on the last page of the article
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Fig. 1 Google Books Ngram Viewer Search Results for: “Innovation” and “Innovators” from 1800 to 2008
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Linguistic sleuthing for innovators
have used the term “innovation” far more than they use the word “innovators,” which has remained relatively flat during that same 200 + year period. In fact, book authors’ use of the word “innovation” is at an all-time high in 20
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