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Update app.py
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app.py
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@@ -127,7 +127,7 @@ with st.expander("Project Description", expanded=False):
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st.write("""
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Developed in Applied Intelligence and Data Analysis ([AI+DA](http://aida.etsisi.upm.es/)) group at Polytech University of Madrid (UPM).
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This tool uses a Spacy-Transformer Name Entity Recognition model to detect the presence of words camouflaged. Word camouflage is currently used to evade content moderation in Social Media. Therefore, the aim of this tool is to counter new ways of misinformation that emerge in social media platforms.
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Currently, two languages are supported: English and Spanish. Additionally, you can select whether the detected entities are broken down into the three types of camouflaged words: Canonical Leetspeak, Punctuation Camouflaged, Inversion Camouflaged. Finally, you can select between "accuracy" or "efficiency" performance.
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""")
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st.write("""
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Developed in Applied Intelligence and Data Analysis ([AI+DA](http://aida.etsisi.upm.es/)) group at Polytech University of Madrid (UPM).
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This tool uses a Spacy-Transformer Name Entity Recognition model to detect the presence of words camouflaged. Word camouflage is currently used to evade content moderation in Social Media. Therefore, the aim of this tool is to counter new ways of misinformation that emerge in social media platforms. This version is a initial step focused on detecting word camouflage in news, reports or talks since the models have been fine-tuned over TED talks, OPUS News Commentaries and Wikipedia.
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Currently, two languages are supported: English and Spanish. Additionally, you can select whether the detected entities are broken down into the three types of camouflaged words: Canonical Leetspeak, Punctuation Camouflaged, Inversion Camouflaged. Finally, you can select between "accuracy" or "efficiency" performance.
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""")
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