Exploring digital narratives: A comprehensive dataset of household energy app reviews.

This paper presents an anonymous dataset of 7999 user reviews covering five household energy mobile applications used in Norwegian households. Such reviews are usually available through the Google Play Store and Apple App Store platforms. They were collected using Python-based Google-Play-Scraper and App Store Scraper. To the best of our knowledge, this dataset represents a unique and valuable resource for investigating sustainable household energy behaviour within the specific context of Norway, where a considerable proportion of households already use these applications. Given the recent rise of mobile applications and the ongoing development of technological infrastructure worldwide, this dataset holds a potential for empirical research. It can provide valuable insights into daily energy practices, user sentiments, perceptions, and motivations for adopting digital solutions. Further, it can shed light on the potential of these solutions to drive sustainable behavioural change. Moreover, conducting the empirical analysis of this dataset can provide valuable insights to stakeholders involved in policy formulation, utility improvement, emissions reduction, and promotion of technology-driven behavioural change.

Comparing sustainable product hashtags: Insights from a historical twitter dataset.

This data article describes the process of data collection and analysis of Twitter conversations about sustainable products. The dataset contains the IDs of tweets tagged with the hashtags #sustainableproducts, #ecoproducts, #ecofriendlyproducts, and #greenproducts. The time period spans 10 years and includes a total of over 140 thousand tweets from around the world. The article describes the process of obtaining the data using Twarc and the Twitter developer's academic researcher API and describes the preprocessing techniques used to identify keywords, hashtags, topics, and sentiments expressed in the conversations. The analysis identifies key attributes of each sustainable product category as well as commonalities and differences within and across categories. The data have the potential to be reused in future research related to sustainable consumption and production, including further analysis of the sentiments and attitudes expressed in the Twitter conversations and comparison with other social media platforms or survey data. In addition, the data can serve as a basis for marketing strategies and product design by enterprises or organizations seeking to promote sustainable products.