Exploring the Music Library Association Mailing List: A Text Mining Approach

Music librarians and people pursuing music librarianship have exchanged emails via the Music Library Association Mailing List (MLA-L) for decades. The list archive is an invaluable resource to discover new insights on music information retrieval from the perspective of the music librarian community. This study analyzes a corpus of 53,648 emails posted on MLA-L from 2000 to 2016 by using text mining and quantitative analysis methods. In addition to descriptive analysis, main topics of discussions and their trends over the years are identified through topic modeling. We also compare messages that stimulated discussions to those that did not. Inspection of semantic topics reveals insights complementary to previous topic analyses of other Music Information Retrieval (MIR) related resources.

[1]  J. Stephen Downie,et al.  Topic Modeling Users' Interpretations of Songs to Inform Subject Access in Music Digital Libraries , 2015, JCDL.

[2]  Gilad Mishne,et al.  Leave a Reply: An Analysis of Weblog Comments , 2006 .

[3]  Andreas Rauber,et al.  Integration of Text and Audio Features for Genre Classification in Music Information Retrieval , 2007, ECIR.

[4]  Richard Griscom.  MLA-L at Twenty , 2009 .

[5]  Michael I. Jordan,et al.  Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..

[6]  Markus Schedl,et al.  Music Information Retrieval: Recent Developments and Applications , 2014, Found. Trends Inf. Retr..

[7]  Yuan-Fang Wang,et al.  The use of bigrams to enhance text categorization , 2002, Inf. Process. Manag..

[8]  J. Stephen Downie,et al.  Improving mood classification in music digital libraries by combining lyrics and audio , 2010, JCDL '10.

[9]  J. Stephen Downie,et al.  An Analysis of ISMIR Proceedings: Patterns of Authorship, Topic, and Citation , 2009, ISMIR.

[10]  J. Stephen Downie,et al.  How People Describe Their Music Information Needs: A Grounded Theory Analysis Of Music Queries , 2003 .

[11]  D. Cox,et al.  SOME QUICK SIGN TESTS FOR TREND IN LOCATION AND DISPERSION , 1955 .

[12]  Melissa Maxwell Edwards,et al.  A content analysis of the PUBYAC discussion list , 1999 .

[13]  J. Stephen Downie,et al.  Toward a Theory of Music Information Retrieval Queries: System Design Implications , 2002, ISMIR.

[14]  William W. Cohen,et al.  Learning to Extract Signature and Reply Lines from Email , 2004, CEAS.

[15]  Deborah Campana.  Information Flow: Written Communication among Music Librarians , 1991 .

[16]  J. Stephen Downie,et al.  WiMIR: An Informetric Study On Women Authors In ISMIR , 2016, ISMIR.

[17]  Andrew McCallum,et al.  The Author-Recipient-Topic Model for Topic and Role Discovery in Social Networks: Experiments with Enron and Academic Email , 2005 .

[18]  John D. Lafferty,et al.  Dynamic topic models , 2006, ICML.

[19]  Jenn Riley,et al.  Ask a Librarian: The Role of Librarians in the Music Information Retrieval Community , 2006, ISMIR.

[20]  N.D. du Preez,et al.  Leveraging unstructured information using topic modelling , 2008, PICMET '08 - 2008 Portland International Conference on Management of Engineering & Technology.

[21]  Daniel Jurafsky,et al.  Studying the History of Ideas Using Topic Models , 2008, EMNLP.

[22]  J. Stephen Downie,et al.  A framework for evaluating multimodal music mood classification , 2017, J. Assoc. Inf. Sci. Technol..

[23]  Ahmed E. Hassan,et al.  What are developers talking about? An analysis of topics and trends in Stack Overflow , 2014, Empirical Software Engineering.

[24]  Jin Ha Lee,et al.  Analysis of user needs and information features in natural language queries seeking music information , 2010, J. Assoc. Inf. Sci. Technol..