One method for clustering stories is to ask story providers to tag their own stories, using tags from a predefined list of tags (plus a free choice of their own). Users of Sensemaker call this self-indexing or self-tagging (see work by Irene Guijt and others). This can help the researcher avoid becoming too locked in by their own pre-conceptions of what each story is about. While the researcher may develop the list of tags, it is left to the story providers to apply them as they see fit.

This tagging data can then be used to find naturally occurring clusters of stories with similar contents. The more tags any two stories share, the more likely their actual content is similar. These clusters can be found using network visualisation software (a method called Participatory aggregation of qualitative information (PAQI) or Network visualisations of qualitative data).  It would be very hard to clusters otherwise although Sensemaker has a device called triads, for doing so, using up to three tags.

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