Text highlighting methodology for consumer attitude measurement: A case study on vertical farming

Attitude measurement occupies a central position in consumer research. Concerns over the validity and reliability of traditional measures have motivated the development of alternative approaches. The present research introduces text highlighting as a method for attitude measurement using a case study on vertical farming (VF). A total of 837 UK consumers participated in an online survey, where they read a text about VF and used highlighting functions to mark text as ‘like’ and ‘dislike.’ Responses were systematic and logical: desirable aspects of VF were frequently highlighted as ‘like’, whereas undesirable aspects were more frequently highlighted as ‘dislike’. These responses were summarised using word clouds, frequency tables and through sentiment scores to reveal an overall positive attitude to VF. Sentiment scores enabled the identification of consumer segments with interpretable differences in their attitude towards VF. Comparison with direct attitude questions and consumer profiling contributed to method validation and further confirmed the potential of this new method. For the former validation approach, the sentiment of specific sentences in the text highlighting task matched results from self-reported attitudes based on Likert scales. Consumer profiling showed that segments with different sentiment scores in the text highlighting task differed in their food technology neophobia scores in the expected direction. Future research should investigate methodological aspects of text highlighting and explore its suitability to other applications.