  The spread of fake news remains a serious global issue; understanding and
curtailing it is paramount. One way of differentiating between deceptive and
truthful stories is by analyzing their coherence. This study explores the use
of topic models to analyze the coherence of cross-domain news shared online.
Experimental results on seven cross-domain datasets demonstrate that fake news
shows a greater thematic deviation between its opening sentences and its
remainder.
