32,518 research outputs found
Technology Assisted Reviews: Finding the Last Few Relevant Documents by Asking Yes/No Questions to Reviewers
The goal of a technology-assisted review is to achieve high recall with low
human effort. Continuous active learning algorithms have demonstrated good
performance in locating the majority of relevant documents in a collection,
however their performance is reaching a plateau when 80\%-90\% of them has been
found. Finding the last few relevant documents typically requires exhaustively
reviewing the collection. In this paper, we propose a novel method to identify
these last few, but significant, documents efficiently. Our method makes the
hypothesis that entities carry vital information in documents, and that
reviewers can answer questions about the presence or absence of an entity in
the missing relevance documents. Based on this we devise a sequential Bayesian
search method that selects the optimal sequence of questions to ask. The
experimental results show that our proposed method can greatly improve
performance requiring less reviewing effort.Comment: This paper is accepted by SIGIR 201
Opening up to big data: computer-assisted analysis of textual data in social sciences
"Two developments in computational text analysis may change the way qualitative data analysis in social sciences is performed: 1. the availability of digital text worth to investigate is growing rapidly, and 2. the improvement of algorithmic information extraction approaches, also called text mining, allows for further bridging the gap between qualitative and quantitative text analysis. The key factor hereby is the inclusion of context into computational linguistic models which extends conventional computational content analysis towards the extraction of meaning. To clarify methodological differences of various computer-assisted text analysis approaches the article suggests a typology from the perspective of a qualitative researcher. This typology shows compatibilities between manual qualitative data analysis methods and computational, rather quantitative approaches for large scale mixed method text analysis designs." (author's abstract
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