Year: 2019
Type: conference-paper
Abstract: The quality of a document is affected by various factors, including grammaticality, readability, stylistics, and expertise depth, making the task of document quality assessment a complex one. In this paper, we explore this task in the context of assessing the quality of Wikipedia articles. Observing that the visual rendering of a document can capture implicit quality indicators that are not present in the document text - such as images, font choices, and visual layout - we propose a joint model that combines the text content with a visual rendering of the document for document quality assessment. Experimental results over a Wikipedia dataset reveal that textual and visual features are complementary, achieving state-of-the-art results. Further experiments on a Peer Review dataset verify the general applicability of our proposed model.
Institution: The University of Melbourne
Language: English
Subfield: Communication
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2967226526