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We present WebNLP, a web-based tool that combines natural language processing (NLP) functionality from Python NLTK and text visualizations from Voyant in an integrated interface. Language data can be uploaded via the website. The results of the processed data are displayed as plain text, XML markup, or Voyant visualizations in the same website. WebNLP aims at facilitating the usage of NLP tools for users without technical skills and experience with command line interfaces. It also makes up for the shortcomings of the popular text analysis tool Voyant, which, up to this point, is lacking basic NLP features such as lemmatization or POS tagging.
We present Sentilyzer, a web-based tool that can be used to analyze and visualize the sentiment of German user comments on Facebook pages. The tool collects comments via the Facebook API and uses the TreeTagger to perform basic lemmatization. The lemmatized data is then analyzed with regard to sentiment by using the Berlin Affective Word List – Reloaded (BAWL-R), a lexicon that contains emotional valence ratings for more than 2,900 German words. The results are visualized in an interactive web interface that shows sentiment analyses for single posts, but also provides a timeline view to display trends in the sentiment ratings.
