Bullshit, Pragmatic Deception, and Natural Language Processing

Fact checking and fake news detection has garnered increasing interest within the natural language processing (NLP) community in recent years, yet other aspects of misinformation remain unexplored. One such phenomenon is `bullshit', which different disciplines have tried to define since it first entered academic discussion nearly four decades ago. bullshitters useless, because factual reality typically plays no part their assertions: Where liars deceive about content, goals. Bullshitting misleading itself, necessitates identifying points at pragmatic conventions are broken with deceptive intent. This paper aims introduce bullshitology into field NLP by tying questions a QUD-based definition, providing two approaches bullshit annotation, finally outlining combinations methods will be helpful classify kinds linguistic bullshit.