Understanding email communication patterns

It has been almost two decades since the beginning of the web. This means that the web is no longer just a technology of the present, but also, a record of our past. Email, one of the original forms of social media, is even older than the web and contains a detailed description of our personal and professional history. This thesis explores the world of email communication by introducing Immersion, a tool build for the purposes to analyze and visualize the information hidden behind the digital traces of email activity, to help us reflect on our actions, learn something new, quantify it, and hopefully make us react and change our behavior. In closing, I look over the email overload problem and work-life balance trends by quantifying general email usage using a large real-world email dataset.

[1]  J. Moreno,et al.  Sociogram and Sociomatrix: A Note to the Paper by Forsyth and Katz , 1946 .

[2]  César A. Hidalgo,et al.  Unique in the Crowd: The privacy bounds of human mobility , 2013, Scientific Reports.

[3]  Alex Pentland,et al.  Reality mining: sensing complex social systems , 2006, Personal and Ubiquitous Computing.

[4]  Vladimir Batagelj,et al.  Pajek - Program for Large Network Analysis , 1999 .

[5]  M. F.,et al.  Bibliography , 1985, Experimental Gerontology.

[6]  Martin Rosvall,et al.  Maps of random walks on complex networks reveal community structure , 2007, Proceedings of the National Academy of Sciences.

[7]  Yusef Hassan-Montero,et al.  Improving Tag-Clouds as Visual Information Retrieval Interfaces , 2024, 2401.04947.

[8]  Jonathan C. Roberts,et al.  Dynamic Coordinated Email Visualization , 2005, WSCG.

[9]  Mark E. J. Newman,et al.  The Structure and Function of Complex Networks , 2003, SIAM Rev..

[10]  Erhard Rahm,et al.  Data Cleaning: Problems and Current Approaches , 2000, IEEE Data Eng. Bull..

[11]  Stanley Wasserman,et al.  Social Network Analysis: Methods and Applications , 1994, Structural analysis in the social sciences.

[12]  Albert-László Barabási,et al.  Statistical mechanics of complex networks , 2001, ArXiv.

[13]  Latanya Sweeney,et al.  k-Anonymity: A Model for Protecting Privacy , 2002, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[14]  Matthew O. Ward,et al.  Interactive Data Visualization - Foundations, Techniques, and Applications , 2010 .

[15]  Mark R. Crispin,et al.  Internet Message Access Protocol - Version 4 , 1994, RFC.

[16]  R. Suganya,et al.  Data Mining Concepts and Techniques , 2010 .

[17]  Jeffrey Heer,et al.  SpanningAspectRatioBank Easing FunctionS ArrayIn ColorIn Date Interpolator MatrixInterpola NumObjecPointI Rectang ISchedu Parallel Pause Scheduler Sequen Transition Transitioner Transiti Tween Co DelimGraphMLCon IData JSONCon DataField DataSc Dat DataSource Data DataUtil DirtySprite LineS RectSprite , 2011 .

[18]  David Easley,et al.  Networks, Crowds, and Markets - Reasoning About a Highly Connected World , 2010 .

[19]  Kwan-Liu Ma,et al.  Visualizing Social Networks , 2011, Social Network Data Analytics.

[20]  Adam Perer,et al.  Contrasting portraits of email practices: visual approaches to reflection and analysis , 2006, AVI '06.

[21]  Roberto J. Bayardo,et al.  Data privacy through optimal k-anonymization , 2005, 21st International Conference on Data Engineering (ICDE'05).

[22]  Martin F. Porter,et al.  An algorithm for suffix stripping , 1997, Program.

[23]  Furu Wei,et al.  Context preserving dynamic word cloud visualization , 2010, 2010 IEEE Pacific Visualization Symposium (PacificVis).

[24]  Mathieu Bastian,et al.  Gephi: An Open Source Software for Exploring and Manipulating Networks , 2009, ICWSM.

[25]  M. Newman,et al.  Finding community structure in very large networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[26]  Charu C. Aggarwal,et al.  An Introduction to Social Network Data Analytics , 2011, Social Network Data Analytics.

[27]  Alex Pentland,et al.  On the Trusted Use of Large-Scale Personal Data , 2012, IEEE Data Eng. Bull..

[28]  M E J Newman,et al.  Modularity and community structure in networks. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[29]  Alex Pentl,et al.  Reality Mining of Mobile Communications: Toward A New Deal On Data , 2009 .

[30]  Martin Wattenberg,et al.  Participatory Visualization with Wordle , 2009, IEEE Transactions on Visualization and Computer Graphics.

[31]  A. J. Bernheim Brush,et al.  Revisiting Whittaker & Sidner's "email overload" ten years later , 2006, CSCW '06.

[32]  Santo Fortunato,et al.  Community detection in graphs , 2009, ArXiv.

[33]  Candace L. Sidner,et al.  Email overload: exploring personal information management of email , 1996, CHI.

[34]  J. Kleinberg,et al.  Networks, Crowds, and Markets , 2010 .

[35]  M E J Newman,et al.  Finding and evaluating community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[36]  Fernanda B. Viégas,et al.  Visualizing email content: portraying relationships from conversational histories , 2006, CHI.

[37]  A. Arenas,et al.  Community detection in complex networks using extremal optimization. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.