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Big Textual Data: Lessons and Challenges for Statistics

Murtagh, Fionn (2017) Big Textual Data: Lessons and Challenges for Statistics. In: SIS 2017 Statistics and Data Science: new challenges, new generations. Proceedings of the Conference of the Italian Statistical Society. Firenze University Press, Florence, Italy, pp. 719-730. ISBN 978-88-6453-521-0

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Abstract

At issue are a few early stage case studies relating to: research publishing and research impact; literature, narrative and foundational emotional tracking; and social media, here Twitter, with a social science orientation. Central relevance and
importance will be associated with the following aspects of analytical methodology: context, leading to availing of semantics; focus, motivating homology between fields of analytical orientation; resolution scale, which can incorporate a concept hierarchy and aggregation in general; and acknowledging all that is implied by this expression: correlation is not causation. Application areas are: research publishing and qualitative assessment, narrative analysis and assessing impact, and baselining and contextualizing, statistically and in related aspects such as visualization.

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Item Type: Book Chapter
Additional Information: Conference keynote presentation.
Uncontrolled Keywords: mapping narrative, emotion tracking, significance of style, Correspondence Analysis, chronological hierarchical clustering
Subjects: H Social Sciences > H Social Sciences (General)
H Social Sciences > HA Statistics
Q Science > QA Mathematics
Q Science > QA Mathematics > QA76 Computer software
Z Bibliography. Library Science. Information Resources > ZA Information resources
Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4050 Electronic information resources
Schools: School of Computing and Engineering
Related URLs:
References:

References

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Depositing User: Fionn Murtagh
Date Deposited: 09 Aug 2017 13:58
Last Modified: 09 Aug 2017 14:08
URI: http://eprints.hud.ac.uk/id/eprint/32545

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