Google Trends Data on Social Communications & Information Activities (April 2021 - March 2026) for Selected Terms, Set#1-3

This record contains Google Trends (GT) time series for English-language terms related to social communications and information activities over the period April 2021 to March 2026. The terms were selected using a multi-level methodology designed to ensure analytical relevance and representativeness across five strategic domains: linguistic technologies, information management, document and archival studies, social communications, and library activities. Only terms with a stable presence in Google Trends were included, while extremely rare and overly dominant queries were excluded in order to improve comparability. To reduce distortions caused by Google Trends normalization, the selected descriptors were grouped into three independent datasets according to their average search frequency: Set #1 (low frequency) contains highly specialized terms: digital resources, citizen science, disinformation, content classification, fact checking, social communications, psychological support, information relations, user data analysis, book publishing, recommendation system, and document flow. Set #2 (medium frequency) contains professional concepts: content strategy, online communication, text analysis, psychological impact, digital technologies, social networks, target audience, public image, volunteering, online advertising, digital communication, social media platform, copywriting, and MOOC. Set #3 (high frequency) contains broader concepts: feedback, information management, information support, digital transformation, open access, social media marketing, state power, transparency, copyright, charity, digital platform, inclusion, online store, online marketing, chatbot, and online education. Data collection was carried out independently for each set. Within each dataset, Google Trends scales all terms relative to a base term (first one in each set) on a normalized 0–100 scale. Separate GT time series for the base terms are also included to support cross-set comparison. These datasets were prepared for the study of structural changes in Google Trends time series and for assessing the methodological validity of GT as a source of digital traces in passive citizen science and related socio-communicative research.