See us in action making the most out of data.

Find here a selection of webinars showing the potential of Graphext in real live situations.

JUNE 19, 2019

Apply data science to transform your marketing analytics

Join Ke and Max to discover best practices from world leading companies. This webinar is in English

MARCH 27, 2019

Machine Learning and Market Research

Join Victoriano and Asier and find out how the top digital marketing agencies use the most advanced ML techniques in their analysis. This webinar is in Spanish.

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Resources

Nuevas perspectivas en analítica y detección de talento: webinar con D'Anchiano

El pasado 15 de julio estuvimos en directo con Juan Palacios, CEO y fundador de D'Anchiano. Juan nos contó en detalle el uso que le da a Graphext para procesos de selección, así como una mayor visibilidad de qué utilidad tiene Graphext y el análisis de datos en RRHH y detección de talento.

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Sentiment Analysis & Billboard Top 100: The Changing Mood of Popular Music

We used sentiment analysis to model 5100 Billboard chart-toppers between 1964 and 2015. Our analysis predicted whether song lyrics were positive, negative or neutral as well as detecting the topic and intent behind the most popular tunes in music history.

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The 5 Most Extreme US Office Characters

Testing out our brand spanking new integration with Hugging Face models for NLP, we analyzed speech from characters in all 9 series of the US Office. Added into our Graphext project, the language models focused on classifying the dialogue of Michael, Dwight, Pam, Jim, Daryll and all the other characters according to the detection of sentiment, emotion, offensive language, irony and hate speech.

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How to Study Brand Conversations with Advanced Text Analysis?

How can we use text analysis of data from Twitter to improve our understanding of markets? This is the question prompting Paul, a strategist in our business team, to scrape tweets about Lloyds bank and conduct a Twitter topic analysis using advanced NLP and network creation. First, he collected tweets using Tractor, Graphext's scraping tool for social media analysis. Then, he analyzed the topics of tweets using network analysis. Here's how he did it ...

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