Approaches to Searching for Language and Diversity in a 'Whitebread City' Digital Corpus: The Charlotte Conversation and Narrative Collection

Macaulay comments that
Dialects, like languages, have both a unifying and a
separatist function. We speak the way we do to be like those we
wish to associate with and to distinguish ourselves from others.
When that association is based on where we live. . . a distinctive
form of speech is likely to survive. However, we need to look at
the whole configuration of linguistic features and not a few features
which may or may not be the critical ones for the speakers.
(239)
Why? In addition to the "grammatical, phonetic, and lexical"
features traditionally posited as characterizing a dialect,
Macaulay adds
prosodic features and possibly also voice quality and discourse
characteristics. There is no reason to believe that dialects have
fewer features than other forms of language, and we do not know
in advance which features will be important to distinguish the
dialect.
(229)
In a discussion of features of southern style that warrant further
investigation, Barbara Johnstone cites several which can be
searched at word- and text-level: these lexicogrammatical
features contribute to the reader/hearer's assessment of style,
and include rhetorical genres triggered by particular discourse
markers; style shifts into regional colloquialism, stylization
and self-parody signaled by shifts into nonstandard verbs, for
example, or a judicious sprinkling of double modals to suggest
temporary intimacy. She asks for an investigation of regional
styles of interacting that "makes strategic use of nostalgia for
neighborhood, local community, or region." (206) Well, they
said southernly, we have a gracious plenty of data that
accommodates such investigation; the issue is, of course, how
to access, identify, and retrieve it.
The corpus that we are using to investigate these questions is
Project MORE's expanded Charlotte Conversation and
Narrative Collection (CNCC), which is part of the 11.5
million-words in the First Release of the American National
Corpus (ANC). Considered a satellite corpus to the core of the
ANC, which parallels the organization of the British National
Corpus (Reppen et al.), the CNCC goal is far more modest, but
still one of difficulty: to create a corpus of conversation and
conversational narration in a New South city at the beginning
of the 21st century. And that, of course, brings us smack up
against issues of region (Macaulay) and representativeness
(Douglas), of dialect diversity (Wolfram & Dannenberg), and
distinctions between rural and metropolitan features (Tillery,
Bailey & Wikle).
The CNCC is hybrid in some ways; similar to the ONZE corpus
in its evolution through multiple formats and purposes (Gordon
et al.). In addition to being a part of the ANC, it is also included
in the New South Voices (NSV) digital resource housed at the
University of North Carolina at Charlotte Library. NSV includes
interviews that cover a wide range of historical subjects, from
African American churches and Billy Graham crusades to
women's basketball and World War II. Other interviews,
narratives and conversations document the experiences and
language of recent immigrants to the area. As such, it seeks to
address a wide variety of audiences from local historians and
historic preservationists to public school students. By using
NSV, we are able to expand the number and range of interviews
available for linguistic as well as for historical analysis.
If the corpus is to be inclusive of the range of spoken styles
that conglomerate in the elastic borders of a New South city,
it must begin by identifying what they are. In today's Charlotte,
today's North Carolina, this is no longer simple. As Tillery,
Bailey & Wykle note, metropolitanization, foreign and domestic
migration, and expanding ethnic diversity have "eliminated
many of the vestiges of traditional regional culture and . . . are
radically reshaping the United States" (228). Their painstaking
study of what they see as the impact of demographic change
on American speech is keyed to 22 socio-demographic and
linguistic variables: 14 phonological features, 3 lexical, and 5
that are lexicogrammatical. They see a balkanization (241; cf
244) with increased divergence of rural and urban ways of
speaking; they ask will "old towns with new populations" —
such as Charlotte — create new communities and new ways of
speaking?
Investigation of these phenomena within a database
environment requires a variety of tools and approaches if we
are to extract the information contained in these transcripts.
The reason for this is due to the nature of the types of information we need to obtain from these interviews and then
to the question of how we can best obtain that information.
On the one hand, we need to be able to perform textual analysis
on the interviews and to examine subjects' speech patterns and
linguistic characteristics. This in turn requires that we be able
to extract information that is embedded within discursive text
— looking at how they use language 'in situ'. On the other hand,
there are discrete pieces of information — metadata if you will
— about the participants (place of origin, current residence,
gender, ethnicity, etc.) to which we need access if we are to do
anything meaningful with what we discover from our textual
analysis. This dichotomy pertains to any area doing textual
analysis. As noted by Ronald Bourrett, the roots of this
dichotomy lie in the two types of information with which we
are dealing: document-centric and data-centric.
Due to the different nature of the two types of information —
linguistic analysis and descriptive metadata — we have found
that a single approach does not allow us to fully explore the
types of correlations we were seeking. While our XML database
allows us to find useful things in searching tagged information
within the interviews, it does not provide sufficient flexibility
in searching data-centric information. On the other hand, with
relational database technology we have exactly the opposite
situation.
In addition, during the course of our investigation, we
discovered that there were certain types of textual information
— such as word- and phrase-frequency; retrieving and isolating
particular words and phrases within their context in a document;
and looking for particular words and/or phrases within certain
proximity of each other — that were amenable neither to an
XML database, nor a classic relational database, approach. To
address this need, we decided that a third option — inverted
indexes — was needed to allow us to look for such patterns.
As noted in Zaïane, this technique greatly enhances the ability
to search textual-based information.
Therefore, in designing our database system, we decided to
adopt a mixed approach, one that allowed us to utilize the
strengths of each system without running afoul of its limitations.
In doing so, we use both XML and inverted indexing to do
textual analysis and then a relational database to correlate that
information with relevant demographic criteria. The result is a
hybrid that allows us to do more than any single approach could
provide.
This paper will first present how we are using readily available
tools to implement a searching system that supports
demographic correlation with textual features (including some
features of proximity search and frequency of occurrence).
These tools, all of which are part of the Open Source tools,
allow us to build and configure with ease a system that not long
ago would require extensive and non-trivial programming. They
include:
• eXist (XML) and MySQL (relational) database managers
• php, perl and Java programming languages
• ApacheWeb server
As a way of concluding, we will then earnestly solicit assistance
on how we can best make this collection of roughly 1,000
transcribed oral interviews, conversations and narratives more
useful to any researcher, particularly in the area of text-based,
online searching.
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