Early detection of emerging research trends could potentially revolutionise the way research is done.
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Amna Dridi, Birmingham City University
Early detection of emerging research trends could potentially revolutionise the way research is done. For this reason, trend analysis has become an area of paramount importance in academia and industry. This is due to the significant implications for research funding and public policy.
The literature presents several emerging approaches to detecting new research trends. Most of these approaches rely mainly on citation counting. While citations have been widely used as indicators of emerging research topics, they suffer from some limitations. For instance, citations can take months to years to progress and then to reveal trends. Furthermore, they fail to dig into paper content.
To overcome this problem, we intend to propose a novel approach to instant detection of research trends that relies on temporal word embeddings (word2vec) to track the dynamics of similarities between pairs of keywords over time which may lead to the detection of emerging trends.
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