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Big Data and Business: Tech mining to capture business interests and activities around big data

Ying Huang, Jan Youtie, Alan L. Porter, Douglas K.R. Robinson

[Abstract]:Tech mining of publications can provide useful intelligence about emerging fields of science and technology in terms of scientific interest and activity. Some breakthrough innovations mature and enter markets at a faster rate than others, sometimes condensing traditional linear s-curves of development to very short time frames. Innovations around Big Data can be characterized as these rapid technology development and deployment dynamics. For this reason, it is necessary to combine tech mining of publication and patent databases with tech mining of business-related databases, to find indications of activities and interests of the business world around Big Data innovation journeys. In this paper, we focus on three commercially oriented databases as candidate sources to extract business ideas: Factiva, LexisNexis and ABI Inform. We select one database to help gauge what are “hot topics” in the business world with regards to big data. Our results show that certain types of firms can be clustered into thematic groups relating to big data discussions and activities. In the paper we demonstrate that such analysis can provide a feel for what themes are being voiced by businesses, and like social media type analyses, they can provide useful intelligence that can inform more in-depth investigation mobilizing other data sources and techniques.

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