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Mining the Social Web by Matthew A Russell

Posted by shawnday on 4 February 2011
Posted in: Social Network Analysis, Text Analysis. Tagged: Data Analysis, O'Reilly, Review. Leave a Comment

mining the social web.gifIn Min­ing the Social Web Mat­thew A Rus­sell offers to instruct in identi­fy­ing social con­nec­tions, trends in dis­cus­sion and loc­a­tions by tap­ping into social media data. He suc­ceeds in spades. This fast-paced and rich hand­book jumps right into the fray and provides an imme­di­ate and use­ful exer­cise in access­ing the Twit­ter API using python and doing a very quick visu­al­isa­tion of trend­ing sub­jects. I was hooked and greed­ily and imme­di­ately con­sumed a few more of his les­sons. His approach is to go dir­ect to real world applic­a­tions of why you’d want to mine data from social media such as Twit­ter, Buzz, Face­book and util­ise other freely avail­able tools such as Google Maps to look for pat­terns and present solid research findings.

As he asserts, all the user needs is some pro­gram­ming back­ground and a will­ing­ness to learn basic Python tools. Fair require­ments. I am no python wiz­ard, but I found clear instruc­tions and come away feel far more com­fort­able with python and avail­able frame­works after pro­ceed­ing through exer­cises in the book. Rus­sell takes you through exer­cises step by step and provides all the instruc­tion neces­sary to guide you along. The book is hands-on heavy and you do have to be will­ing to play along with goodly chunks of code. This is not a light browsable book. Although it does allow for some skip­ping about, it is the sort of volume that engages with the reader/practitioner and nat­ur­ally leads you along. The exer­cises do assume some degree of back­ground with data ana­lysis. Although expressed in as simple a lan­guage as pos­sible, cer­tainly when get­ting into nat­ural lan­guage pro­cessing for example, some back­ground in gen­eral terms, pro­cesses and meth­od­o­lo­gies in NLP are expec­ted. How­ever, this should not put any­one off and I was impressed that this formed a quick and use­ful intro­duc­tion to the craft because Rus­sell does such a superb job of root­ing the the­ory in every­day lan­guage and practice.

I was sim­il­arly impressed with the authors inclu­sion of exer­cises in min­ing your own mail­box for use­ful ana­lysis and how to con­duct nat­ural lan­guage pro­cessing on blog feeds, not just stick­ing with the sex­ier and trend­ier flashy social media tools today. This is a very com­pre­hens­ive and thought­ful approach to the ava­lanche of explor­able data avail­able from our social exist­ence and Rus­sell provides an extremely approach­able and superbly craf­ted volume. For any­one inter­ested in step­ping bey­ond simple par­ti­cip­a­tion and tak­ing a thought­ful view of how social media is chan­ging our lives, this is the book of ref­er­ence. What’s more I really just simply enjoyed this book. Highly recommended!

I review for the O'Reilly Blogger Review Program


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  • about.me

    Shawn Day

    Shawn Day

    Shawn Day is an entrepreneur, digital historian, economist and blender of the aesthetic and the informative. Raised in Canada, Shawn now works with the Digital Humanities Observatory, a project of the Royal Irish Academy, to leverage Ireland's participation in the emerging practise of digital humanities scholarship. He lectures in Social Computing and the Philosophy of Technology.

    His own research explores the social and economic circumstances of the nineteenth century retail liquor trade and it's impact on family. He applies digital, spatial and social network analysis to the study of the relationships between credit, respectability, and order in the Victorian community. Recent articles have examined the social dimensions of the Victorian public mental hospital using GIS and statistical modeling tools. Shawn has been involved in a number of successful and innovative digital humanities projects throughout Canada. Most recently he has worked with large manuscript census databases in the 1871/1891 census project (University of Guelph). He is a team member of the national TAPoR text analysis portal project, the Canadian Network for Economic History and the Network for Canadian History and the Environment (NiCHE - UWO).

    Shawn has blended his background in management economics with an entrepreneurial ethos to found a number of successful software development ventures in Canada and find a means to leverage this in the academic arena.

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      • Conference Papers
      • Datasets
        • 1871 Populations of Ontario
        • 1871 Tavernkeepers in Huron County
        • Breweries and Distilleries in Ontario, 1914–15
        • Canadian Federal Railway Charters
      • Maps
        • 1841 Settlers Map of Ontario
        • 1848 Circulation Map of Paris
        • 1851 Essex County by Religion Stated in Census
        • 1891 Ontario Census Divisions
        • Admissions from Gaols to Hamilton Asylum
        • Asylums in New Zealand, 1900
        • Asylums in Scotland, 1797–1897
        • Asylums in the Australian Colonies, 1860
        • Asylums in the United States, 1850
        • Asylums in Western Canada, 1911
        • Asylums of England and Wales, 1765–1845
        • Asylums of England and Wales, 1845–1860
        • Asylums of Ireland, 1814–1869
        • Discharge Rate from Hamilton Asylum
        • Duration of Stay for First Admissions to Hamilton Asylum
        • First Admissions to Hamilton Asylum by County
        • Irish and Indian-Trained Psychiatrists in Canada
        • Modern Circulation Map of Paris
        • Rate of Readmission to Hamilton Asylum
        • Study Context
      • Other Research Stuff
        • Sir Frank Smith
      • Visual Support Materials
        • 1851 — 1911 Essex County Census District Evolution
        • 1878 Guelph Mass Model
        • Guelph Historical GIS
        • Napoleonic Timeline
        • Occupational Comparison 1867–2007
        • Pajek Apple Taxonomy
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