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Exploratory novelty identification in human activity data streams

Published: 02 November 2010 Publication History

Abstract

Heterogeneous human-generated data streams are the measurands which provide opportunities to identify patterns, detect novelties and explore evolution of complex social systems. Communication technologies with their very high penetration into society can serve as particularly rich sources of information. However, for a variety of observable communication channels one has little or no access to the content of human-to-human communications, while the data streams on the intensities of such events are more common. The paper presents a framework of methods useful for exploratory analysis and visualization of such data streams. Particularly, we demonstrate how untypical activity levels can be identified by fitting a non-homogeneous Markov-modulated Poisson process and spatialising the component corresponding to unusual bursts/lulls of activity via heat maps. This approach is illustrated with a case study devoted to the analysis of geo-referenced data streams of instant messaging activity on the internet.

References

[1]
A. S. Fotheringham and D. W. S. Wong. The modifiable areal unit problem in multivariate statistical analysis. 23(7):1025--1044, 1991.
[2]
A. Ihler, J. Hutchins, and P. Smyth. Adaptive event detection with time-varying poisson processes. In KDD '06: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 207--216, New York, NY, USA, 2006. ACM.
[3]
A. Pozdnoukhov. Dynamic network data exploration through semi-supervised functional embedding. In GIS '09: Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, pages 372--379, New York, NY, USA, 2009. ACM.
[4]
B. W. Silverman. Density Estimation for Statistics and Data Analysis. Chapman and Hall/CRC, 1 edition, April 1986.
[5]
R. L. Wolpert and K. Ickstadt. Poisson/gamma random field models for spatial statistics. Biometrika, 85(2):251--267, June 1998.

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  • (2021)The rhythms of the night: increase in online night activity and emotional resilience during the spring 2020 Covid-19 lockdownEPJ Data Science10.1140/epjds/s13688-021-00262-110:1Online publication date: 1-Feb-2021
  • (2018)GeoStreamsACM Computing Surveys10.1145/317784851:3(1-37)Online publication date: 23-May-2018
  • (2013)Temporal analysis of activity patterns of editors in collaborative mapping project of OpenStreetMapProceedings of the 9th International Symposium on Open Collaboration10.1145/2491055.2491068(1-4)Online publication date: 5-Aug-2013
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  1. Exploratory novelty identification in human activity data streams

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    cover image ACM Conferences
    IWGS '10: Proceedings of the ACM SIGSPATIAL International Workshop on GeoStreaming
    November 2010
    67 pages
    ISBN:9781450304313
    DOI:10.1145/1878500
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 02 November 2010

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    Author Tags

    1. Poisson processes
    2. machine learning
    3. novelty detection

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    Overall Acceptance Rate 7 of 9 submissions, 78%

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    View all
    • (2021)The rhythms of the night: increase in online night activity and emotional resilience during the spring 2020 Covid-19 lockdownEPJ Data Science10.1140/epjds/s13688-021-00262-110:1Online publication date: 1-Feb-2021
    • (2018)GeoStreamsACM Computing Surveys10.1145/317784851:3(1-37)Online publication date: 23-May-2018
    • (2013)Temporal analysis of activity patterns of editors in collaborative mapping project of OpenStreetMapProceedings of the 9th International Symposium on Open Collaboration10.1145/2491055.2491068(1-4)Online publication date: 5-Aug-2013
    • (2012)Circadian Patterns of Wikipedia Editorial Activity: A Demographic AnalysisPLoS ONE10.1371/journal.pone.00300917:1(e30091)Online publication date: 17-Jan-2012
    • (2011)Space-time dynamics of topics in streaming textProceedings of the 3rd ACM SIGSPATIAL International Workshop on Location-Based Social Networks10.1145/2063212.2063223(1-8)Online publication date: 1-Nov-2011

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