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Showing posts with the label #ExtractingStreetFoodData

Web Scraping Street Food Data: Identify Emerging Culinary Preferences

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  How Does Web Scraping Street Food Data Help Identify Emerging Culinary Preferences? Street food is something more than a snack on the go. It can be an ethnocultural experience beyond just filling one's stomach. Indeed, the demand for authentic, tasty, and affordable food brought about an explosion in street food markets worldwide. In the United States, the street vendor industry could reach $4.2 billion by 2024, achieving a compound annual growth rate of 13.3%. The trend has been hastened by economic factors such as inflation only because consumers increasingly seek meals that satisfy their appetites and come with great value and convenience. Global street food trends shift toward indulgence and affordability as trends emerge from the cuisines of Filipino and Cambodian street foods. These foods have given consumers something to desire—something bold and unique in flavor yet deeply rooted in a culture that both represent. Businesses and researchers are looking to use web scraping ...