Automatic detection of critical plot information in reviews of media items poses unique challenges to both social computing and computational linguistics. In this paper we propose to cast the problem of discovering spoiler bias in online discourse as a text simplification task. We conjecture that for an item-user pair, the simpler the user review we learn from an item summary the higher its likelihood to present a spoiler. Our neural model incorporates the advanced transformer network to rank the severity of a spoiler in user tweets. We constructed a sustainable high-quality movie dataset scraped from unsolicited review tweets and paired with a title summary and meta-data extracted from a movie specific domain. To a large extent, our quantitative and qualitative results weigh in on the performance impact of named entity presence in plot summaries. Pretrained on a split-and-rephrase corpus with knowledge distilled from English Wikipedia and fine-tuned on our movie dataset, our neural model shows to outperform both a language modeler and monolingual translation baselines.

Research on analyzing reading patterns of dyslectic children has mainly been driven by classifying dyslexia types offline. We contend that a framework to remedy reading errors inline is more far-reaching and will help to further advance our understanding of this impairment. In this paper, we propose a simple and intuitive neural model to reinstate migrating words that transpire in letter position dyslexia, a visual analysis deficit to the encoding of character order within a word. Introduced by the anagram matrix representation of an input verse, the novelty of our work lies in the expansion from one to a two dimensional context window for training. This warrants words that only differ in the disposition of letters to remain interpreted semantically similar in the embedding space. Subject to the apparent constraints of the self-attention transformer architecture, our model achieved a unigram BLEU score of 40.6 on our reconstructed dataset of the Shakespeare sonnets.