Link to the publisher's web site

Provision of data and of some R software, and in a few cases, other software, is with the following objective: to facilitate learning by doing, i.e. carrying out analyses, and reproducing results and outcomes. That may be both interesting and useful, in parallel with the more methodology-related aspects that can be, and that ought to be, revealing and insightful.

Chapter 1

• Related to subsection 1.2.4: A Small Example Using the Casablanca Movie Script
• Casablanca-scene-description.csv - data used.
• Just for information: locations.txt, the locations of each scene.
• The analysis: analysis-Casablanca-scenes-by-characters.txt.

• Related to subsection 1.2: Casablanca Movie Script
• scenes01to77_textfiles.zip, 77 text files, from the Casablanca movie script, for each scene.
  all77fileswords.txt, full extracted word list.
  xtabulate-scene77.txt, cross-tabulation of 77 scenes by a corpus of 2654 words.
  
• scene43_11textfiles.zip, 11 text files, for the subscenes of scene 43.
  all43fileswords.txt, full extracted word list.
  xtabulate-scene77.txt, cross-tabulation of 11 subscenes, from movie scene 43, by a corpus of 210 words.
• readdatatables.txt, reading the two previous data tables into R.

• Related to subsection 1.3: Research Funding
• section1pt3.zip, research centres and clusters, with descriptions in separate text files, the set of all words extracted, allwords.txt, and the cross-tabulation of centres/clusters by years, institutes and themes. data5678.txt, from the years 2005 ... 2008, cross-tabulation of RFP, Research Frontiers Programme projects crossed by years, institute, and themes.

• Related to subsection 2.1: Twitter
• ch2twitter.zip, containing 302 tweets as separate text files, the list of 1787 words, allwords.txt, and the cross-tabulation of tweets by words, xtab.txt

• Related to subsection 2.4: CSI Las Vegas
• CSI101.zip, 50 scenes in individual text files, 1679 word list in allwords.txt, and two cross-tabulations of the scenes with word sets.

• Related to subsection 2.6: Commodity Fetishism
• commodityfetishm.zip, 21 paragraphs as individual text files, allwords.txt list of 974 words extracted, and cross-tabulation of paragraphs by words.
• commodityfetishm2.zip, seven selected paragraphs, allwords.txt list of 482 words, and cross-tabulation of paragraphs by words.

Chapter 3

• Related to subsection 3.3: Tables 3.1, 3.2 and Fig. 3.2
• R processing (text file), and Fig. 3.2.
• Related to subsection 3.6.3: Haar wavelet transform of a dendrogram
• haarum.r. Hierarchical Haar wavelet transform in R (see commented lines at start for example of use, using Fisher's iris data), which works on a hierarchy produced by a hierarchical clustering program. This hierarchical Haar wavelet transform carries out the following processing tasks: (i) from the data and a hierarchy, produce the wavelet transform; (ii) filter the wavelet coefficients, using a user-specified hard threshold; and (iii) reconstruct the data, i.e. perform the inverse wavelet transform.

Chapter 5

• Related to subsection 5.1: Identifying ultrametricity of 1D signals. (F. Murtagh, "Identifying the ultrametricity of time series", European Physical Journal B, 43, 573-579, 2005.)
• The program used in this work: equil-time-series.c Also needed is nrutil.h for a few definitions. Examples of use:
  equil-time-series 1326 2 ftse1326.dat
  (Input time series ftse1326.dat; number of values to be read, 1326, must be equal to, or less than, the number of values in the file; and the value of 2, number of categories used in the coding, should be fixed always at 2.)
  equil-time-series 1326 2 r
  (Use 1326 uniformly distributed random values.)
  • FTSE (1326)
  • USD/EUR (1169)
  • Sunspots (2739)
  • Stock (1374)
  • Eyegaze (1471)
  • EEG-chan4 (2500)
  • EEG-chan5 (2500)
  • Futures (6160)
  • Server bytes (34,726)
  • Mississippi (43829)

• Related to subsection 5.2: Random projection, clustering, Baire metric
• File with listing of all processing. All background and R code, text file. File to read for all software, data, processing.
• Datasets.
  • rBCI1052encoded.scn.zip (All chemicals data, 53 MB, unzipped > 500 MB)
  • testdata1k2k.txt.zip (1000 chemicals)
  • BCI1052enc7500.dat.zip (7500 chemicals)
• Software.
  • Program to extract data from the BCI-encoded chemical dataset: ExtractBCI.c
    Compile and link using: gcc -lm ExtractBCI.c -o ExtractBCI
  • Used in processing in R, repeatedly carry out random projections and determine their mean: RepeatRanProj.r
  • Slimmed down Correspondence Analysis program: ca-projonly.r
  • Just drawing in a factor plane projection: plaxes.r
• Output plots. (See full description in the background description above.)
  • sample-output-hist1.pdf
  • sample-output-hist2.pdf
  • sample-output-CA-1.pdf
  • sample-output-convergence-mean-ranproj.pdf
  • sample-output-convengence-mean-ranproj-2.pdf
  • sample-output-histograms.pdf
  • sample-output-display.pdf
  • sample-output-CA1000.pdf
  • sample-output-PCA-9cluster-centres.pdf
  • sample-output-kmeans-PCA-9cluster-centres.pdf
  • sample-output-loglogplot.pdf
• Some Further Data Sets.
  • doc_similarities.mm.zip (document similarities, > 22 MB).
  • redshifts5000.dat.zip (5000 astronomical redshifts ).

Chapter 6

• Annex to Chapter 6: High Dimensional Simulations: Uniform, Financial, Chemical.
• Chap6Annex.txt Chapter 6 Annex.
• ob5x.csv, financial signal.
• inputdata.txt, chemical data.

Chapter 7

• Annex to Chapter 6: High Dimensional Simulations: Uniform, Financial, Chemical.
• face-reconstruction.txt Generating data for the faces, clustering them and wavelet transforming the dendrogram. Then reconstructing the face data.
• haarum.r Haar wavelet transform of a dendrogram, with an option to carry out filtering in the sparsified, wavelet transform space.
• faces.R, display data as Chernoff faces. (Ad hoc program, to be improved.)

Chapter 8

• Section 8.1.3 Determining Depth of Emotion, and Tracking Emotion, and some other data sets. .
• Dialogue between Ilsa and Rick in key scenes in the Casablanca movie. CSV file..
• From Chapters 9 to 12 of Flaubert's Madame Bovary, 22 successive text segments. Zip file containing 22 text files.
• Twitter flows from New York Times, Le Monde, Guardian, Irish Times, Süddeutsche Zeitung. The original of each of these 1000-tweet flows, and the tweet texts alone, saved from R as .RData files. A readme file describes the setting up of these files.
• Subtitles of the film Casablanca, in English, French, German.
  • Casablanca-film-subtitles.csv, Casablanca film subtitles, csv file.
  • Casablanca-film-sous-titres.csv, sous-titres du film, Casablanca, fichier csv.
  • Casablanca-Film-untertitel.csv, Untertitel des Films, Casablanca, Datei csv.

Chapter 10

• Big Data Analytics:
  • Using Apache Lucene,
  • Semantic Vectors,
  • Mahout,
  • Solr, using:
  • Classification Literature Automated Search Service (Here the data from Volume 23, with 1994 data, to Volume 41, with 2012 data, are available. In this data, there are 93,191 bibliographic records.),
  • Data Analysis of Cooking Recipes (152,998 recipes), Availing both of R and Solr.
• Access all here: From this web page. [ Note: currently access requires a password. Here are the details, name: Courses ; and the password consists of three letters, a number, and then four letters, as one word: Wel 1 Come ]

Most recent update: 2017 October 29. Updated were: (i) Under "Chapter 10", the link now has access details written here; (ii) Under "Related to subsection 5.2", "Software", a .c program and three .r scripts are now accessible. (iii) Under "Chapter 5", the link to nrutil.h is accessible.