Article navigation
Purpose

The purpose of this paper is to develop a visualization method for texts produced by a company's competitors, partners, or customers. This method can be used for competitive intelligence purposes, and in particular, for spotting changes over time in a company's communication.

Design/methodology/approach

Based on the judgments of expert readers, topics considered to be important in the quarterly reports of two telecommunication companies were turned into so‐called collocational networks, using a statistical method originating in linguistics.

Findings

The paper shows that when collocational topic networks are produced out of a sequence of quarterly reports, they provide a visualization of how the presentation of these topics changes from one‐quarter to the next.

Research limitations/implications

The statistical method used in this paper does not handle low‐frequency topics, that nevertheless might be of great importance, very well. The method could be developed further so that users' judgments of importance are given more weight.

Practical implications

The method developed in this paper can be turned into a data visualization tool for intelligence practitioners.

Originality/value

Textual data are often overlooked in competitive intelligence, as it is more difficult to visualize and present than quantitative data, such as financial ratios. The method presented here is an easy to grasp “white box” approach to visualizing textual data, as it combines the judgments of subject matter experts with a statistical method.

You do not currently have access to this content.
Don't already have an account? Register

Purchased this content as a guest? Enter your email address to restore access.

Pay-Per-View Access
$39.00
Rental

or Create an Account

Close Modal
Close Modal