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Computer Support for Frame
 Analysis of Media Content:




                                             Yuwei Lin, 15 Jan 2009, MeCCSA 2009, Bradford, UK
Some Methodological Thoughts

              Yuwei Lin
ESRC National Centre for e-Social Science,
         University of Manchester
          http://www.ncess.ac.uk
Acknowledgement
 JISC-funded 18-month TMFA Project:




                                                    Yuwei Lin, 15 Jan 2009, MeCCSA 2009, Bradford, UK
  Using Text Mining for Frame Analysis of Media
  Content
 Key members: Sophia Ananiadou, June Finch,
  Peter Golding, Peter Halfpenny, Thomas Koenig,
  Yuwei Lin, Elisa Pieri, Rob Procter, Brian Rea,
  Farida Vis, Davy Weissenbacher (in alphabetical
  order)
Outline
 A STS-informed
  paper on the impact




                          Yuwei Lin, 15 Jan 2009, MeCCSA 2009, Bradford, UK
  of computerisation on
  doing social research
 Challenges of frame
  analysis
 Text mining
  technologies
 Some methodological
  issues
 Concluding remarks
Challenges of Frame Analysis
 Labour-intensive manual coding




                                                Yuwei Lin, 15 Jan 2009, MeCCSA 2009, Bradford, UK
 Error-prone, biased, subjective/interpretative
 Non-scalable (small corpora): difficult to deal
  with increasingly large amount of data
 Solutions: More analysts (but low inter-coder
  reliability) or Computerising the analysis
 Trend of bridging the long-standing tension
  between quantitative (statistics) and
  qualitative (meanings) methods
Yuwei Lin, 15 Jan 2009, MeCCSA 2009, Bradford, UK
Text-mining
  the opportunity of processing large amounts of
  textual data systematically, reducing human
  errors, and saving time
  the potential to at least partly automate the
  generation of frames
  add-on feature to Computer-Assisted Qualitative
  Data Analysis Software (CAQDAS) packages
Some Methodological Thoughts
 Does corpus size matter?




                                                  Yuwei Lin, 15 Jan 2009, MeCCSA 2009, Bradford, UK
    Conceptual validity and generalisability
 Whose interpretations / what assumptions?
    Conceptual validity and generalisability
 Levels of meanings
    Conceptual validity and generalisability
 Standardisation of units of measurements
    Clarity and transparency in doing analysis
Does corpus size matter?
 Corpus building: small but focused, or




                                                Yuwei Lin, 15 Jan 2009, MeCCSA 2009, Bradford, UK
  large, noisy but indiscriminative
 What to include in a corpus?
 How to reduce noise in raw data?
 Where does human interpretation end?
 Does corpus size have any impact on the
  conceptual validity and generalisability of
  frames? (quantitative or qualitative)
Whose interpretations and
      what assumptions?
 Manual coding results may be subjective,




                                                    Yuwei Lin, 15 Jan 2009, MeCCSA 2009, Bradford, UK
  interpretative, biased.
 In the case of computer-supported
  analysis:
   which text mining algorithms/techniques to
   adopt?
   based on which techniques (statistical ones?)
   and on which training datasets?
   These techniques and corpora reflect certain
   interpretations, assumptions and world views.
Levels of meanings in frames
 Diversity in doing frame analysis and




                                              Yuwei Lin, 15 Jan 2009, MeCCSA 2009, Bradford, UK
  different definitions of frames
 Various types of frames: multiple frames,
  overlapping frames, frames that shape
  people's actions and their involvement in
  everyday activities (Goffman)
 How applicable are the lexical
frames extracted by text mining
techniques?
Standardisation of Units of
         Measurements




                                                  Yuwei Lin, 15 Jan 2009, MeCCSA 2009, Bradford, UK
 Frames exist in different levels: words,
  sentences, paragraphs, articles (units of
  measurement)
 Interpretative flexibility in manual coding
 Debate on clarity and transparency
 Text mining is systematising and
  standardising the units of measurement.
   More objective? More reliable? More biased?
   More transparent or more black-boxed?
Concluding remarks
 Labour-intensive, error-prone manual coding




                                                  Yuwei Lin, 15 Jan 2009, MeCCSA 2009, Bradford, UK
 CAQDAS (particularly those with text mining)
 Methodological issued posed by
  computerisation:
   Does corpus size matter?
   Whose interpretations and what assumptions?
   Levels of meanings in frames
   Standardisation of units of measurements
 Depending on research questions & contexts

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Some Methodological Thoughts on Using Text Mining for Frame Analysis of Media Content

  • 1. Computer Support for Frame Analysis of Media Content: Yuwei Lin, 15 Jan 2009, MeCCSA 2009, Bradford, UK Some Methodological Thoughts Yuwei Lin ESRC National Centre for e-Social Science, University of Manchester http://www.ncess.ac.uk
  • 2. Acknowledgement  JISC-funded 18-month TMFA Project: Yuwei Lin, 15 Jan 2009, MeCCSA 2009, Bradford, UK Using Text Mining for Frame Analysis of Media Content  Key members: Sophia Ananiadou, June Finch, Peter Golding, Peter Halfpenny, Thomas Koenig, Yuwei Lin, Elisa Pieri, Rob Procter, Brian Rea, Farida Vis, Davy Weissenbacher (in alphabetical order)
  • 3. Outline  A STS-informed paper on the impact Yuwei Lin, 15 Jan 2009, MeCCSA 2009, Bradford, UK of computerisation on doing social research  Challenges of frame analysis  Text mining technologies  Some methodological issues  Concluding remarks
  • 4. Challenges of Frame Analysis  Labour-intensive manual coding Yuwei Lin, 15 Jan 2009, MeCCSA 2009, Bradford, UK  Error-prone, biased, subjective/interpretative  Non-scalable (small corpora): difficult to deal with increasingly large amount of data  Solutions: More analysts (but low inter-coder reliability) or Computerising the analysis  Trend of bridging the long-standing tension between quantitative (statistics) and qualitative (meanings) methods
  • 5. Yuwei Lin, 15 Jan 2009, MeCCSA 2009, Bradford, UK Text-mining  the opportunity of processing large amounts of textual data systematically, reducing human errors, and saving time  the potential to at least partly automate the generation of frames  add-on feature to Computer-Assisted Qualitative Data Analysis Software (CAQDAS) packages
  • 6. Some Methodological Thoughts  Does corpus size matter? Yuwei Lin, 15 Jan 2009, MeCCSA 2009, Bradford, UK  Conceptual validity and generalisability  Whose interpretations / what assumptions?  Conceptual validity and generalisability  Levels of meanings  Conceptual validity and generalisability  Standardisation of units of measurements  Clarity and transparency in doing analysis
  • 7. Does corpus size matter?  Corpus building: small but focused, or Yuwei Lin, 15 Jan 2009, MeCCSA 2009, Bradford, UK large, noisy but indiscriminative  What to include in a corpus?  How to reduce noise in raw data?  Where does human interpretation end?  Does corpus size have any impact on the conceptual validity and generalisability of frames? (quantitative or qualitative)
  • 8. Whose interpretations and what assumptions?  Manual coding results may be subjective, Yuwei Lin, 15 Jan 2009, MeCCSA 2009, Bradford, UK interpretative, biased.  In the case of computer-supported analysis:  which text mining algorithms/techniques to adopt?  based on which techniques (statistical ones?) and on which training datasets?  These techniques and corpora reflect certain interpretations, assumptions and world views.
  • 9. Levels of meanings in frames  Diversity in doing frame analysis and Yuwei Lin, 15 Jan 2009, MeCCSA 2009, Bradford, UK different definitions of frames  Various types of frames: multiple frames, overlapping frames, frames that shape people's actions and their involvement in everyday activities (Goffman)  How applicable are the lexical frames extracted by text mining techniques?
  • 10. Standardisation of Units of Measurements Yuwei Lin, 15 Jan 2009, MeCCSA 2009, Bradford, UK  Frames exist in different levels: words, sentences, paragraphs, articles (units of measurement)  Interpretative flexibility in manual coding  Debate on clarity and transparency  Text mining is systematising and standardising the units of measurement.  More objective? More reliable? More biased? More transparent or more black-boxed?
  • 11. Concluding remarks  Labour-intensive, error-prone manual coding Yuwei Lin, 15 Jan 2009, MeCCSA 2009, Bradford, UK  CAQDAS (particularly those with text mining)  Methodological issued posed by computerisation:  Does corpus size matter?  Whose interpretations and what assumptions?  Levels of meanings in frames  Standardisation of units of measurements  Depending on research questions & contexts