How can the development of ideas in a scientific field be studied over time ? We apply unsupervised topic modeling to the ACL Anthology to analyze historical trends in the field of Computational Linguistics from 1978 to 2006 . We induce topic clusters using Latent Dirichlet Allocation , and examine the strength of each topic over time . Our methods find trends in the field including the rise of probabilistic methods starting in 1988 , a steady increase in applications , and a sharp decline of research in semantics and understanding between 1978 and 2001 , possibly rising again after 2001 . We also introduce a model of the diversity of ideas , topic entropy , using it to show that COLING is a more diverse conference than ACL , but that both conferences as well as EMNLP are becoming broader over time . Finally , we apply Jensen-Shannon divergence of topic distributions to show that all three conferences are converging in the topics they cover . How can we identify and study the exploration of ideas in a scientific field over time , noting periods of gradual development , major ruptures , and the waxing and waning of both topic areas and connections with applied topics and nearby fields ? One important method is to make use of citation graphs ( Garfield , 1955 ) . This enables the use of graphbased algorithms like PageRank for determining researcher or paper centrality , and examining whether their influence grows or diminishes over time . However , because we are particularly interested in the change of ideas in a field over time , we have chosen a different method , following Kuhn ( 1962 ) . In Kuhn 's model of scientific change , science proceeds by shifting from one paradigm to another . Because researchers ' ideas and vocabulary are constrained by their paradigm , successive incommensurate paradigms will naturally have different vocabulary and framing . Kuhn 's model is intended to apply only to very large shifts in scientific thought rather than at the micro level of trends in research foci . Nonetheless , we propose to apply Kuhn 's insight that vocabulary and vocabulary shift is a crucial indicator of ideas and shifts in ideas . Our operationalization of this insight is based on the unsupervised topic model Latent Dirichlet Allocation ( LDA ; Blei et al . ( 2003 ) ) . For many fields , doing this kind of historical study would be very difficult . Computational linguistics has an advantage , however : the ACL Anthology , a public repository of all papers in the Computational Linguistics journal and the conferences and workshops associated with the ACL , COLING , EMNLP , and so on . The ACL Anthology ( Bird , 2008 ) , and comprises over 14,000 documents from conferences and the journal , beginning as early as 1965 through 2008 , indexed by conference and year . This resource has already been the basis of citation analysis work , for example , in the ACL Anthology Network of Joseph and Radev ( 2007 ) . We apply LDA to the text of the papers in the ACL Anthology to induce topics , and use the trends in these topics over time and over conference venues to address questions about the development of the field . Despite the relative youth of our field , computational linguistics has witnessed a number of research trends and shifts in focus . While some trends are obvious ( such as the rise in machine learning methods ) , others may be more subtle . Has the field gotten more theoretical over the years or has there been an increase in applications ? What topics have declined over the years , and which ones have remained roughly constant ? How have fields like Dialogue or Machine Translation changed over the years ? Are there differences among the conferences , for example between COLING and ACL , in their interests and breadth of focus ? As our field matures , it is important to go beyond anecdotal description to give grounded answers to these questions . Such answers could also help give formal metrics to model the differences between the many conferences and venues in our field , which could influence how we think about reviewing , about choosing conference topics , and about long range planning in our field . Our method discovers a number of trends in the field , such as the general increase in applications , the steady decline in semantics , and its possible reversal . We also showed a convergence over time in topic coverage of ACL , COLING , and EMNLP as well an expansion of topic diversity . This growth and convergence of the three conferences , perhaps influenced by the need to increase recall ( Church , 2005 ) seems to be leading toward a tripartite realization of a single new " latent " conference .
How topics or ideas have developed over time in NLP community remains unknown while there are analysis over the ACL anthology citation graph. 
They propose to use Latent Dirichlet Allocation for studying topic shift over time and a model to compute the diversity of ideas and topic entropy.
They found that COLING has more diversity than ACL, but all the conferences are becoming to cover more topics over time, and applications increase generally.