Time Series Analysis of Discourse | Agenda Bookshop Skip to content
A01=Dennis Tay
Age Group_Uncategorized
Age Group_Uncategorized
AR Model
ARMA Model
Author_Dennis Tay
automatic-update
Category1=Non-Fiction
Category=CFF
Category=CFG
Category=CFGR
Category=PBT
CDA Practitioner
Consecutive Lectures
Contemporary Societies
COP=United Kingdom
Corpus Assisted Discourse Studies
Delivery_Pre-order
Dennis Tay
discourse analysis
Discourse Phenomena
eq_dictionaries-language-reference
eq_isMigrated=2
eq_non-fiction
Language_English
MA Model
MA Process
metaphor studies
MIP
Multivariate TSA
Object Relations Therapy
PA=Temporarily unavailable
PACF
Partial Autocorrelation
Price_€20 to €50
PS=Active
Psychotherapy Talk
Random Walk
Random Walk Model
Random Walk Processes
Real Observed Data
Residual Series
Seasonal ARIMA
Seasonal Time Series Model
Shapiro Wilk Statistics
softlaunch
Time Series Analysis
Time Series Model
time-based discourse
variationist sociolinguistics
Vice Versa

Time Series Analysis of Discourse

English

By (author): Dennis Tay

This volume serves as a comprehensive introduction to Time Series Analysis (TSA), used commonly in financial and engineering sciences, to demonstrate its potential to complement qualitative approaches in discourse analysis research. The book begins by discussing how time has previously been conceptualized in the literature, drawing on studies from variationist sociolinguistics, corpus linguistics, and Critical Discourse Analysis. The volume then segues into a discussion of how TSA is applied in other contexts in which observed values are expected to be dependent on earlier values, such as stock markets and sales figures, and introduces a range of discourse-specific contexts to show how the technique might be extended to analyze trends or shed further light on relevant themes in discourse over time. Each successive chapter features a different discourse context as a case study, from psychotherapy sessions, university lectures, and news articles, and looks at how studying different variables over time in each context – metaphors, involvement markers, and keywords, respectively – can contribute to a greater understanding of both present and future discourse activity in these settings. Taken together, this book highlights the value of TSA as a complementary approach to meaning-based analysis in discourse, making this ideal reading for graduate students and scholars in discourse analysis looking to employ quantitative methods in their research practice.

See more
€27.50
A01=Dennis TayAge Group_UncategorizedAR ModelARMA ModelAuthor_Dennis Tayautomatic-updateCategory1=Non-FictionCategory=CFFCategory=CFGCategory=CFGRCategory=PBTCDA PractitionerConsecutive LecturesContemporary SocietiesCOP=United KingdomCorpus Assisted Discourse StudiesDelivery_Pre-orderDennis Taydiscourse analysisDiscourse Phenomenaeq_dictionaries-language-referenceeq_isMigrated=2eq_non-fictionLanguage_EnglishMA ModelMA Processmetaphor studiesMIPMultivariate TSAObject Relations TherapyPA=Temporarily unavailablePACFPartial AutocorrelationPrice_€20 to €50PS=ActivePsychotherapy TalkRandom WalkRandom Walk ModelRandom Walk ProcessesReal Observed DataResidual SeriesSeasonal ARIMASeasonal Time Series ModelShapiro Wilk StatisticssoftlaunchTime Series AnalysisTime Series Modeltime-based discoursevariationist sociolinguisticsVice Versa

Will deliver when available.

Product Details
  • Weight: 240g
  • Dimensions: 138 x 216mm
  • Publication Date: 18 Dec 2020
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Language: English
  • ISBN13: 9780367732677

About Dennis Tay

Dennis Tay is an Associate Professor at the Department of English, The Hong Kong Polytechnic University. His research interests include cognitive linguistics, discourse analysis, mental healthcare communication, and the statistical modeling of discourse.

Customer Reviews

Be the first to write a review
0%
(0)
0%
(0)
0%
(0)
0%
(0)
0%
(0)
We use cookies to ensure that we give you the best experience on our website. If you continue we'll assume that you are understand this. Learn more
Accept