Our first classification task was to train the classifier on the 54,289 articles that were assigned categories of knowledge by the editors of the Encyclopédie and to then apply this model to the 22,796 unclassified articles in an attempt to predict class membership for the articles in question. Once classified, the twenty most frequent labels for the newly classified articles were: While this distribution of classes bears some resemblance to the overall distribution cited above, we have no real way of verifying the accuracy of the classifier given the unknown content/classes of the unclassified articles.[11] While it is entirely plausible that 19% of the unclassified articles are concerned with Jurisprudence in a general sense, it is also likely that Jurisprudence (which represents only 5% of the classified articles) becomes of sort of “catch-all” category for the classifier into which articles concerned with any specific aspect of law (i.e. droit romain, droit canonique, droit civil, etc.) are grouped.

The sample of results we examined reveal that the classifier performed reasonably well. By this, we mean that some classifications seemed right on; some made a good degree of sense, while others were perhaps a bit too general, failing to accurately represent the specificity of the subject matter. Naturally, the more than 22,000 newly generated classifications could not all be verified by hand, and so we focused on major articles and a selection of smaller ones. We were particularly encouraged by the assigned classifications for the 10 longest unclassified articles. The Discours Préliminaire, d'Alembert's famous preface to the Encyclopédie detailing the intellectual underpinnings of the enterprise, comes back as belonging to the class Philosophy.[12] Going down the list we see that the article “Anatomie” is assigned its own classification in Anatomy and “Chimie” is rightly placed into Chemistry, results we had originally hoped were easy enough for the algorithm to attain. Most of the classifications, however, don't fall into such clear categories. For example, “Venerie” — the art of hunting — was assigned to Natural History; the philosophical article “Eclectisme” to the History of Philosophy, etc. Indeed, while these and the better part of the predicted classifications can be justified on a general level, we had to concede that the overall utility of this task was somewhat questionable. Quite simply, as we mention above, there was just too much data to sort through. The new labels were often interesting, but we were not able to study them easily or thoroughly enough to come to any deeper understanding about how the philosophes structured knowledge or indeed how the Encyclopédie itself fits together. Thus, trying to develop an experiment that could generate more legible results, we decided instead to leverage the information given us by the editors in exploring the known classifications and their relationship to each other and then later, to consider the classification scheme as a whole by examining the general distribution of classes over the entire work as opposed to individual instances.

Having run a set of predictive classification experiments on the unclassified articles, our next task was an attempt at what we have named "comparative" classification, wherein we train the classifier on two particular classes, and then reclassify them in an effort to determine how separable they are and to ascertain which features best distinguish articles from the two sets. The goal here has less to do with the accuracy of the classifications than with the feature sets that are generated during the classification task. Any two classes can be compared. Feature weights are generated using the Naive Bayes Perl module written by Ken Williams. These weights represent the conditional probability of a feature f given a class c and are generated based on their frequency in the known articles.[13] To give an example of this sort of comparative classification, 889 articles classified as “Histoire ancienne” were compared with 1194 articles in the “Histoire moderne” class and the following features and their weights were extracted as the most relevant in determining class membership: The overall performance of the classifier came in at 95.63%, which tells us that while both belong to the same “branch” of science, namely History, the ancient and the modern are nonetheless significantly distinguishable from one another. When considering the two lists of features, one immediately notices that the results make good sense, i.e., we find more verbs in the past tense ( avoient , étoient, etc.) in the Ancient History articles as well as references to antiquity ( romains , empereur, rome, etc.). The single-letter feature “g” is the signature of the Abbé Mallet who was the author of a significant portion of the articles on Ancient History. Interestingly, some of the features occur in both lists, which is more than likely a result of the close relationship and dialogue between the two classes. In the feature set for Modern History, we find references to forms of government that quite rightly belong to the modern period ( état, prince, roi, chevalier, etc.) and the notable absence of the word “ dieu ” (“god”).

We can also run comparative classification tasks on seemingly dissimilar classes of knowledge such as the 682 Literature articles and the 200 articles dealing with Physics. Not surprisingly, we obtain a very high rate of success for this sort of classification, in this case, 99.29%:

The feature scores from this model are what we would expect. The Literature class' most significant features are those words pertaining to language and grammar ( mot, livre, vers, auteur, latin, usage, etc.) whereas the Physics class is dominated by materialistic terminology ( corps, air, eau, degré, fluide, mouvement, etc.) consistent with the scientific writings of the period.

Evaluation of these feature sets can be invaluable when testing certain hypotheses, such as word usage differences across similar disciplines or between authors. In this particular case, the features provide an intuitive illustration of the differences between these two distinct classes of knowledge. While features are simply terms that the algorithm finds statistically representative of a particular class, the feature sets as a whole can also give a snapshot of the make-up of the individual classes or indeed of larger concepts more generally. From the list for literature, for example, we get a sense of the importance that classical Roman authors still had for the philosophes with the terms “ancien” (“ancient”) and latin. “Vers” (“verse”) perhaps reflects the fact that versification was a predominant aspect of literary style, whether in poetic, dramatic, and other writing at that time. Terms such as “mot” (“word”) and “usage” (“use”) might point to the 18th century's expansive, belle-lettristic sense of literature that we discuss below. In a more general manner, feature sets provide us with an expanded thesaurus for any given classification task -- leads for further investigation and study -- that can then be exploited by a more traditional full text analysis system.[14]

Finally, we applied the model assembled for our first experiment — trained on all of the known classifications — onto all of the already classified articles. By this, we mean that we effectively ignored any given classes of knowledge, treating each article as if it were unclassified, and then assigned class membership using the algorithm described above. Here our goal in the results analysis was twofold: first, we were curious as to the overall performance of our classification algorithm, i.e., how well it correctly labeled the known articles; and secondly, we wanted to use these new classifications to examine the outliers or misclassified articles in an attempt to understand better the presumed coherency and consistency of the editors' original classification scheme.

We achieved a 71.4% success rate in the re-categorization of the 54,289 classified articles, a performance that could perhaps be improved with a more accurate morphological stemmer and the inclusion of n-grams as features, fucnctions we intend to implement in the future. Nonetheless, developing a model to reliably guess an article's given class of knowledge is ultimately not our primary concern as even a perfect model, while impressive in terms of performance, could only yield that which we already know, namely the assigned classes of knowledge. The sheer size and complexity of the Encyclopédie, drawing its contents from hundreds of distinct writers, all but guarantees a lower rate of performance for any classification algorithm. This fact need not be discouraging however, as we are more interested in exploring the use of these text mining techniques as knowledge discovery tools, uncovering previously unnoticed connections and classifications, such as the particular use of the class “Literature” outlined below, rather than simply using these approaches as a statistical platform for hypothesis testing.

The twenty most frequent classes after re-classification:

When comparing the results to the original classifications we note that the class “Grammar” falls out of the top ten while “Art méchanique,” which is not included in the original top twenty, ranks as the sixth most frequent class. The Grammar class is known to be problematic as Diderot frequently used this seemingly innocuous label to hide more polemical entries.[15] As for the “Art méchanique” category, we suspect that many of the overly specific classes dealing with the mechanical arts were subsumed into this larger, more inclusive set. By and large the rest of the classes are consistent with the overall distribution in the Encyclopédie although the rankings differ slightly.

The most interesting results here come from the examination of misclassified articles, which belie vocabularies that do not belong probabilistically to their assigned categories. Upon analyzing a random subset of the misclassified articles, we identified three distinct types of misclassifications. First, there are articles whose original classification was too infrequent; for example, the article “Accrues” (metal rings used to knit together fishing net) is the sole member of the class “Marchands de Filets” (net merchants) and was placed into the more general class of “Pêche” (fishing). There are also articles whose vocabularies mislead the classifier. One such case is the article “Achées” (a type of worm used in bait-fishing), originally classified as “Pêche,” it was later assigned to the class “Jardinage” (gardening). The article is in fact less a description of anything to do with fishing, but rather contains instructions on how to find and cultivate bait worms in a garden. Finally, there are entries whose predicted class, while incorrect, seems more logical than the original. The article “Tepidarium,” which describes an ancient Roman bathhouse, would appear to have more in common with its predicted class, Architecture, than the one assigned by the editors, namely Literature. Certainly our judgment that the predicted class is more appropriate than the original class of knowledge is biased by our modern epistemological paradigm, but this does not necessarily mean that the original system of classification was entirely consistent and coherent. Naturally then, applying our model onto other 18th century French texts should provide further insight into the power of the classifier and more importantly, into the ontology originally laid out by the philosophes.

The Journal de Trévoux, or Mémoires pour l'Histoire des Sciences & des Beaux-Arts, was one of the most influential 18th century French periodicals. A sort of literary/scholarly journal reviewing and commenting on a wide variety of contemporary publications, the Journal de Trévoux dealt with almost every discipline of knowledge. Given the great variety of subject matter contained in this collection we felt it would be a natural choice for us to begin studying the relationship of the Encyclopédie ontology to other 18th century texts. Of course, the 18th century in France was a time of intellectual ferment and, as in most historical moments, there existed more than one approach to the classification of the known world. And, indeed, the philosophes' intellectual and political bent made their way of organizing ideas different from that of other thinkers, particularly the Jesuits who were behind the Journal de Trévoux. Knowing this, we wanted to test the degree of overlap between the structure of knowledge in the Encyclopédie and the Journal de Trévoux, discovering in the process the commonalities, differences, and unique aspects of each. We hoped this experiment would give us a "slice of life" look at the intellectual milieu of the day, or at least provide an insight into the presumed differences in discourse between the two camps. To this end, we processed the ARTFL Project's 109 volumes of the Journal de Trévoux, splitting them into 1,027 separate articles. Extending from 1751 to 1757, this collection covers the years during which the editors of the Journal engaged in a fierce polemic with the encyclopédistes concerning the publication of the Encyclopédie.[16] Our previous model, trained on all of the classified Encyclopédie articles, was thus applied to the Trévoux articles, assigning each with a predicted class of knowledge. The twenty most frequent assigned classes are listed below:

A cursory glance at these results gives us a general idea about the most significant themes found in the Journal de Trévoux; themes that correspond nicely to our preconceived notions concerning the Journal, its writers and subject matter. Along these lines, it is not surprising to find in a Jesuit publication such as this a greater emphasis on articles about Literature, Morality, Theology, and Philosophy. However, the surprising fact that more than 1/3 of the 1000 articles were assigned the label of Littérature caused us to question somewhat the performance of the classifier and ultimately, to reconsider our modern notion of Literature when applied to the specific instances of this classification.

In the first edition (1694) of the Dictionnaire de l'Académie française the entry for “Littérature” reads thus: “ Litterature. s. f. Erudition, doctrine. Grande litterature. profonde litterature. il est homme de grande litterature. il n'a point de litterature. il a beaucoup de litterature. ” and indeed the definition changes little by the fourth edition of 1762: “ LITTÉRATURE. s.f. Érudition, doctrine. Grande littérature. Profonde littérature. Il est homme de grande littérature. N'avoir point de littérature. Avoir beaucoup de littérature. Un ouvrage plein de littérature. Ce mot regarde proprement les Belles-Lettres. ” The addition of the last sentence, “This word is properly used in regard to Belles Lettres,” in the 1762 edition seemingly restricts this particular form of erudition to the more traditionally literary realm of the “Belles-Lettres,” or Poetry and Rhetoric. The definition offered by the Jesuit editors of the Dictionnaire de Trévoux (1742) differs only slightly from that of the Academy: “LITTÉRATURE, s. f. Doctrine, connoissance profonde des Lettres. Doctrina, litteratura, eruditio.” While these definitions shed little light as to why the Encyclopédie literature class should be so prevalent in the classification of such a diverse collection of articles, many of which deal with the Sciences and Natural History, the ambiguity of this erudite possession of “ littérature ” and “ lettres ” should nonetheless cause us to broaden our understanding of these terms as they were used in the mid-18th century.

We thus began a more thorough investigation of the Literature category by examining five randomly selected articles belonging to the assigned class “Littérature” in the Journal de Trévoux. While some categorizations make sense as literature — e.g., the article “Nouvelles Litteraires,” a sort of literary “news of the day”; and, less convincingly, a commentary on Rousseau's first discourse — others have ostensibly nothing to do with our modern idea of Literature — e.g., articles commenting on a history of jurisprudence, a treatise on diseases, and a compilation of treatises on Physics and Natural History[17]. This apparent anomaly necessarily leads us back to the Encyclopédie and the articles belonging to the class of knowledge Literature, which serve as the basis for these class assignments.

As we mentioned above concerning the reclassification of the article “Tepidarium,” there are a great many articles whose original classifications seem inappropriate. This phenomenon is all the more evident when examining the reclassification of the Literature articles, the majority of which deal more with Ancient History, Mythology, and Architecture than with accepted literary issues. Of the 682 Literature articles, 460 were written by the Chevalier de Jaucourt, author of more than 17,000 Encyclopédie entries. Jaucourt is known to have borrowed extensively from other sources and thus, we attributed these inconsistencies to intellectual laziness, given the enormous number of articles for which he was responsible.[18] Upon closer examination of the Literature class of knowledge however, this characterization proves unjust.

Indeed, the article titled “Littérature” belongs not to its own class of knowledge, but rather to three seemingly unrelated and disparate classes: Sciences, Belles-Lettres, and Antiquity. The text of the article, written by Jaucourt, is in fact a polemic advocating a universal erudition and an expanded definition of what it means to possess a great literature — in a word to be literate. Jaucourt includes a renvoi to the article “Lettres” in an effort to define better this notion of Literature. Following the cross-reference we find that the article in question, “Lettres,” an article that normally falls innocuously amongst numerous similarly titled entries, is the sole member of the class “Encyclopédie,” suggesting that the idea of literacy is essential to the entire encyclopedic enterprise. Here, Jaucourt's understanding of “Lettres” as a much larger category of knowledge than “belles-lettres” or even the Humanities as a whole (les lettres humaines), harkens back to the Classical acceptation of the term which encompassed all areas of human understanding from Epic Poetry to Physics. The inter-connectedness of knowledge, both literary and scientific, is thus the essence of Jaucourt's idea of encyclopedic literacy, wherein “ il en résulte que les lettres & les sciences proprement dites, ont entr'elles l'enchaînement, les liaisons, & les rapports les plus étroits; c'est dans l'Encyclopédie qu'il importe de le démontrer ” (“the result is that Letters and Sciences, properly speaking, have between each other a strong and direct network of links and relationships; it is in the Encyclopaedia that the demonstration of this network becomes important”).[19]