Which statement is NOT true about topic modelling within the domain of text analytics?

$$ Topic models help the users to argue which topics are appropriate.

Topic models can organize, understand and summarize large collections of textual information.

Topic modelling can be done by different techniques, such as: Latent Dirichlet Allocation $($LDA$),$ Latent Semantic Analysis $($LSA$),$ Correlated Topic Models $($CTM$)$ and TextRank.

$$ Topic models discover hidden topical patterns that are present across the collection.

Topic Modeling is how the machine collects group of words within a document to build 'topic' which contain group of words with similar dependencies.