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Driving engagement through emotional content: a data-driven analysis from the Upworthy Research Archive: understanding online engagement - a multi layered analysis of digital engagement drivers
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Orientador(es)
Resumo(s)
In a digital landscape where capturing reader attention is crucial to news platforms, the
Upworthy Research Archive enables the study of how article headlines influence engagement.
This research assesses how the components of a headline impacts user clicks through machine
learning methods to extract features related to emotional and phrase-meaning topics to predict
the level of engagement on each piece of news. Results show that timing dominates
engagement, headline structure plays a key role, and emotional traits have limited influence.
Additional analysis explores how headline characteristics impacts Upworthy’s engagement.
Descrição
Palavras-chave
Digital content Engagement Upworthy MIND Prediction News articles Headline Excerpt Categories Classification algorithms Machine learning Natural language processing User interaction Content strategy Interaction trends Patterns Insights Text embeddings Forecasting Time series Clickbait detection Headline classification Text analysis Clickbait trends Plots Statistical analysis t-Test t-Test Hypothesis testing Model evaluation