The online argumentation platform SolAr, which combines aspects of online argumentation and social media as a modern approach to embed arguments within a social network, is a modular application implemented with Django. The modular design and generalized core of SolAr allows versatile use for a wide variety of questions and research projects. While social media rely on a variety of search functions, systems of online argumentation mostly use simple text searches. There are versatile search methods available which, like recommendation systems, are based on relevance and can capture differences, and despite the highly individual evaluations of users, can carry forward generalized suggestions.
Therefore, SolAr should be extended by a module to objectively search and process relevant arguments based on their content, structure and additional properties.
For SolAr to be extended with an objective search considering relevant arguments, the following points must be met:
- reviewing existing and generally accepted literature
- familiarization with SolAr, Django, Elasticsearch and individual libraries for solving the problem
- implementation of the knowledge gained from point 1 and 2
- testing, documenting and integration into SolAr
Overall, SolAr is to be expanded to include an objective search to consider relevant arguments.
Recommended previous knowledge
Interest in data analysis, natural language processing, web development, databases, programming and online argumentation
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