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  • The #dariahTeach Project
  • The IGNITE Project
Testimonials
  • Introduction
  • Unit I: Definitions
  • Unit II: Corpus linguistics & Language
  • Unit III: Text analytics and language
  • Unit IV: Applications / workflows
  • Unit IV: Applications / workflows

    This final unit contains a few use cases showcasing the methods discussed in the OER. While we have provided you with concrete examples, the intention is for you to be able to work through the use cases provided here, and then apply those new skills to your own area of interest.




    • 4.1. Sentiment analysis on Twitter Lesson
    • 4.2. Topic Modeling Future Stories For Europe Lesson
◄Unit III: Text analytics and language
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Introduction
  Text Analysis - Linguistics Meets Data Science
  • Introduction
  • What is Text Analysis and Why Bother?
  • A Dimpah OER
  • Intended Learning Objectives
  • Teaching and Learning Methods
  • Instructions
Unit I: Definitions
  1.1. Linguistic research perspectives
  • 1.1.1. Computational analysis of text
  • 1.1.2. Linguistic research using computers
  • 1.1.3. What is a corpus?
  • 1.1.4. Linguistic perspectives to data science
  1.2. Data science research perspectives
  • 1.2.1. Data Science Research Perspectives
  • 1.2.2. Sample vs. Population
  • 1.2.3. Sampling
  • 1.2.4. Preprocessing of Texts: Stop words
  • 1.2.5. Preprocessing of texts: stemming, lemmatisation, annotation
  • 1.2.6. Linguistics and Data Science Quiz
  1.3. Tools of the trade(s)
  • 1.3.1. Tools of the Trade(s)
  • 1.3.2. Data Science Tools
  • 1.3.3. Corpus Linguistic Tools
  • 1.3.4. Programming
  • 1.3.5. Tools of the Trade(s) Quiz
  • 1.3.6. Our Tool of Choice: KNIME
  Linguistics and Data Science Quiz
  Tool quiz
Unit II: Corpus linguistics & Language
  2.1. Concordances, tagging, and annotation
  • 2.1.1. What are concordances?
  • 2.1.2. Formulating queries
  • 2.1.3. Part of Speech tagging
  • 2.1.4. Manual pruning and classification of corpus results
  2.2. Patterns in language and text
  • 2.2.1. Collocations
  • 2.2.2. Collocation networks
  • 2.2.3. Semantic prosodies
  • 2.2.4. Words, Sentences and Paragraphs
  • 2.2.5. N-grams, lexical bundles and other sequential patterns
  • 2.2.6. Keywords
  2.3. Registers and text types
  • 2.3.1. Registers
  • 2.3.2. Text types
  • 2.3.3. Corpus Linguistics & Language Quiz
  Corpus linguistics and Language Quiz
  2.4. Frequency, distribution and inferential statistics
  • 2.4.1. Frequency
  • 2.4.2. Distribution
  • 2.4.3. From descriptive to inferential statistics
  • 2.4.4. Statistical significance and effect size
Unit III: Text analytics and language
  3.1. Text analytics and language
  • 3.1.1. Text analytics and language
  • 3.1.2. Machine learning and pattern identification
  3.2. Sentiment analysis
  • 3.2.1. Lexicon-based sentiment analysis
  • 3.2.2. Machine learning and sentiment analysis
  3.3. Topic Modelling
  • 3.3.1. Topic modelling
  • 3.3.2. Topic modelling in KNIME
  3.4. Text Classification
  • 3.4.1. Text Classification
  • 3.4.2. Text Classification in KNIME
  • 3.4.3. Authorship Attribution
  • 3.3.4. Text Analytics & Language Quiz
  Text Analytics and Language Quiz
Unit IV: Applications / workflows
  4.1. Sentiment analysis on Twitter
  • 4.1.1. Overview of workflow
  • 4.1.2. Acquiring the Tweets
  • 4.1.3. Performing Sentiment Analysis
  • 4.1.4. Results
  4.2. Topic Modeling Future Stories For Europe
  • 4.2.1. Overview of workflow
  • 4.2.2. Document Preprocessing
  • 4.2.3. Text Preprocessing
  • 4.2.4. Topic Modeling and Visualisation
  • 4.2.5. Results
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      • Text Analysis: Linguistic Meets Data Science

        • Participants

        • Introduction

        • Unit I: Definitions

        • Unit II: Corpus linguistics & Language

        • Unit III: Text analytics and language

        • Unit IV: Applications / workflows

          • Lesson4.1. Sentiment analysis on Twitter

          • Lesson4.2. Topic Modeling Future Stories For Europe

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Main Language

en

Other Languages

aa

Publisher Name

dariahTeach

Authors

Jukka Tyrkkö, Daniel Ihrmark

Licence

CC-BY-SA

Publication Date

2023-05-22 16:20:00

ECTS

5

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