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 .

Challenge: How topics or ideas have developed over time in NLP community remains unknown while there are analysis over the ACL anthology citation graph. 
Approach: 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.
Outcome: 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.