This presentation aims to analyze liminal divisions in 4 collections of ELTeC (Spanish, French, Romanian, and English) and to propose a functional definition of the introductory units based on their sentiment profiles. In the first part, we briefly introduce theories of prefaces as paratext and emphasize the fact that their repertory of devices has been estimated as being much more stable than readers and authors themselves would believe (Genette 1987, 161-292; Peikola & Bös 2020, 3-33; Rolls & Barcan 2011, 13-26, 137-157, Pelatt 2013, 3-33). Beside a predictable repertory of tropes (mentioned in all treatises of rhetoric), prefaces are related to “moments”, thus to pathetic “intensity”, a feature that opens up a path for SA explorations. After the theoretical remarks, we explain the preprocessing steps such as: distinction between author, editor and allographic prefaces; distinction among original, later, and delayed prefaces; separation of a novel’s various introductory units in distinct files; the lower limit of words for the textual units considered for analysis; the cleaning-up of data (normalization and translation where necessary). In a second part, we link types of liminal divisions (prefaces, epigraphs, dedications, and other) with ELTeC metadata, so as to see if gender, time period, length or reprint count have an influence on the number and type of liminal texts. Even if this paper is based on a more limited number of collections, we are particularly interested in determining whether, as in the case of ELTeC titles (Patras et al., 2021), there are zones of cultural influence. In the third part, we focus on the prefaces, because they are the longest amongst liminal units. Rather than listing their pragmatic functions and describe their “empirical historicity” within a close reading approach (Genette 1987, 162), we use sentiment analysis tools to see if their global “sentiment outline” can be related to momentous intensity and to specific tasks (Barros et al 2013; Evgeny et al 2019; Harshita & Mirza 2018) such as previewing/ summarizing, commenting/ explaining, and contextualizing the novels. Unfortunately, no tool supports actually the four languages we intend to work upon. To overcome this difficulty, we use first two different tools (Lingmotif – [www.lingmotif.com]) and the Python library TextBlob, on the English and the Spanish collection (English and Spanish are supported by both tools). We confront the results, then apply TextBlob on French, and Lingmotif on translations of Romanian texts (produced with DeepL https://www.deepl.com/translator, then checked with Rowordnet sentiment attributes http://dcl.bas.bg/bulnet/). While this method has several disadvantages (use of different tools, of translated texts), it also has the advantage of allowing us both to sketch a new definition to the prefatory genre and to test the robustness of a “combine-and-adapt” approach, which is (and will be for some more time) the day-to-day reality of computer literary studies.