Abstract
Data are currently characterized as the world’s most valuable resource and agriculture is responding to this global trend. The challenge in that particular field of study is to create a Digital Agriculture that help the agri-food sector grow in a fair, competitive environment. As automated machine learning techniques and big data are global research trends in agronomy, this paper aims at comparing different marketing techniques based on Content Analysis to determine the feasibility of using Twitter to design marketing strategies and to determine which techniques are more effective, in particular, for the strawberry industry. A total of 2249 hashtags were subjected to Content Analysis using the Word-count technique, Grounded Theory Method (GTM), and Network Analysis (NA). Findings confirm the results of previous studies regarding Twitter’s potential as a useful source of information due to its lower execution and analysis costs. In general, NA is more effective, cheaper, and faster for Content Analysis than that based both on GTM and automated Word-count. This paper reveals the potential of strawberry-related Twitter data for conducting berry consumer studies, useful in increasing the competitiveness of the berry sector and filling an important gap in the literature by providing guidance on the challenge of data science in agronomy.
Highlights
Data are currently characterized as the world’s most valuable resource, or the oil of the digital era [1]
With the overall aim of using different techniques to discover the main topics included in tweets that included the hashtags #strawberries or #fresas, and assess the potential of Twitter data for consumer marketing research, we focus on the following research questions: RQ1: “Does the content of hashtags associated with the search criteria reflect the interests of the strawberry consumer?”; RQ2: “Do non-explicit relationships among consumers’ hashtags reflect different and more-or-less relevant topics of interest for berry-industry?”; and RQ3: “Which hashtag Content Analysis technique has been more effective?”
Social tags are analyzed, which serve as mechanisms for the semantic unification of concepts within a social network [56,57], as Twitter is based on short messages—less than 280 characters
Summary
Data are currently characterized as the world’s most valuable resource, or the oil of the digital era [1]. It is trying to create digitization strategies that will enable and catalyze a Digital Agriculture and that help the agri-food sector grow in a fair competitive environment. 90% of marketing specialists consider Social Networks Sites (SNSs) to be important for their marketing strategy [5], because of their becoming an important channel for communications with consumers due to the large volume of users and the possibility of collecting data directly from them. Social media marketing is an inexpensive alternative to traditional methods of involving consumers [3,6,7,8]. This is especially significant for small- and medium-sized enterprises since their resources, including marketing budgets, are usually smaller than those of their larger counterparts [9]. The agribusiness literature still lags in this field [3,10]
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