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Ethnography in the virtual world: Methodological opportunities and challenges

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ESS Digital Sociology Conference presentation.

I provide an overview of methodological opportunities, challenges, and solutions to consider for sociologists who are thinking about delving into the world of online ethnography.

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Ethnography in the virtual world: Methodological opportunities and challenges

  1. 1. Ethnography in the Virtual World: Methodological Opportunities and Challenges Gina Marie Longo, ABD University of Wisconsin-Madison
  2. 2. Mapping out the discussion • The research • The methodological opportunities of Virtual Ethnography • The methodological challenges of Virtual Ethnography • Some proposed solutions to methodological challenges
  3. 3. Mapping out the discussion • The research • The methodological opportunities of Virtual Ethnography • The methodological challenges of Virtual Ethnography • Some proposed solutions to methodological challenges
  4. 4. Mapping out the discussion • The research • The methodological opportunities of Virtual Ethnography • The methodological challenges of Virtual Ethnography • Some proposed solutions to methodological challenges
  5. 5. Mapping out the discussion • The research • The methodological opportunities of Virtual Ethnography • The methodological challenges of Virtual Ethnography • Some proposed solutions to methodological challenges
  6. 6. Mapping out the discussion • The research • The methodological opportunities of Virtual Ethnography • The methodological challenges of Virtual Ethnography • Some proposed solutions to methodological challenges
  7. 7. The Research Project • examines how US citizens’ experiences with the spousal reunification process affect their enacted citizenship and how they are informed by normative conceptions of family, gender, race, and class that treat some relationships as morally suspect. • It also investigates how U.S. citizens negotiate deservingness and marital genuineness when facing the state’s moral evaluation, and how these negotiations vary across gender, race, class, and region.
  8. 8. The Research Project • Examines how US citizens’ experiences with the spousal reunification process affect their enacted citizenship and how they are informed by normative conceptions of family, gender, race, and class that treat some relationships as morally suspect. • It also investigates how U.S. citizens negotiate deservingness and marital genuineness when facing the state’s moral evaluation, and how these negotiations vary across gender, race, class, and region.
  9. 9. The Research Project • Examines how US citizens’ experiences with the spousal reunification process affect their enacted citizenship and are informed by normative conceptions of family, gender, race, and class that treat some relationships as morally suspect. • It also investigates how U.S. citizens negotiate deservingness and marital genuineness when facing the state’s moral evaluation, and how these negotiations vary across gender, race, class, and region.
  10. 10. Immigration Pathways The Data Source • a large English-language self- help forum • Created in the early 2000’s • Over 2.2 million conversation threads • Multiple sub-forums • Over 100,000 members Collection and Analysis • Ethnographic Immersion • Web scraping • Quantitative Content Analysis of themes and members • Qualitative Analyses of Conversation Threads
  11. 11. Immigration Pathways The Data Source • a large English-language self- help forum • Created in the early 2000’s • Over 2.2 million conversation threads • Multiple sub-forums • Over 100,000 members Collection and Analysis • Ethnographic Immersion • Web scraping • Quantitative Content Analysis of themes and members • Qualitative Analyses of Conversation Threads
  12. 12. Immigration Pathways The Data Source • a large English-language self- help forum • Created in the early 2000’s • Over 2.2 million conversation threads • Multiple sub-forums • Over 100,000 members Collection and Analysis • Ethnographic Immersion • Web scraping • Quantitative Content Analysis of themes and members • Qualitative Analyses of Conversation Threads
  13. 13. Immigration Pathways The Data Source • a large English-language self- help forum • Created in the early 2000’s • Over 2.2 million conversation threads • Multiple sub-forums • Over 100,000 members Collection and Analysis • Ethnographic Immersion • Web scraping • Quantitative Content Analysis of themes and members • Qualitative Analyses of Conversation Threads
  14. 14. Immigration Pathways The Data Source • a large English-language self- help forum • Created in the early 2000’s • Over 2.2 million conversation threads • Multiple sub-forums • Over 100,000 members Collection and Analysis • Ethnographic Immersion • Web scraping • Quantitative Content Analysis of themes and members • Qualitative Analyses of Conversation Threads
  15. 15. Immigration Pathways The Data Source • a large English-language self- help forum • Created in the early 2000’s • Over 2.2 million conversation threads • Multiple sub-forums • Over 100,000 members Collection and Analysis • Ethnographic Immersion • Web scraping • Quantitative Content Analysis of themes and members • Qualitative Analyses of Conversation Threads
  16. 16. Immigration Pathways The Data Source • a large English-language self- help forum • Created in the early 2000’s • Over 2.2 million conversation threads • Multiple sub-forums • Over 100,000 members Collection and Analysis • Ethnographic Immersion • Web scraping • Quantitative Content Analysis of themes and members • Qualitative Analyses of Conversation Threads
  17. 17. Immigration Pathways The Data Source • a large English-language self- help forum • Created in the early 2000’s • Over 2.2 million conversation threads • Multiple sub-forums • Over 100,000 members Collection and Analysis • Ethnographic Immersion • Web scraping • Quantitative Content Analysis of themes and members • Qualitative Analyses of Conversation Threads
  18. 18. Immigration Pathways The Data Source • a large English-language self- help forum • Created in the early 2000’s • Over 2.2 million conversation threads • Multiple sub-forums • Over 100,000 members Collection and Analysis • Ethnographic Immersion • Web scraping • Quantitative Content Analysis of themes and members • Qualitative Analyses of Conversation Threads
  19. 19. Immigration Pathways The Data Source • a large English-language self- help forum • Created in the early 2000’s • Over 2.2 million conversation threads • Multiple sub-forums • Over 100,000 members Collection and Analysis • Ethnographic Immersion • Web scraping • Quantitative Content Analysis of themes and members • Qualitative Analyses of Conversation Threads
  20. 20. Immigration Pathways The Data Source • a large English-language self- help forum • Created in the early 2000’s • Over 2.2 million conversation threads • Multiple sub-forums • Over 100,000 members Collection and Analysis • Ethnographic Immersion • Web scraping • Quantitative Content Analysis of themes and members • Qualitative Analyses of Conversation Threads
  21. 21. Methodological Opportunities 1. Innovative Access  accessing hidden or scattered communities 2. Conversation candidness Participants openly discuss a variety of topics that vary across and within subject matter There is less self-censoring and more frankness in utterances Removes the researcher’s influence on participants’ interactions 3. Spatial and temporal comparison Archived conversations demonstrate how topics and perspective shift over time The sub-forum divide allows me to analyze how topics and perspectives shift across sub-groups of people 4. Endless research project opportunities Seemingly endless possibilities for future projects  This is particularly useful for carving a long-term research agenda
  22. 22. Methodological Opportunities 1. Innovative Access  accessing hidden or scattered communities 2. Conversation candidness Participants openly discuss a variety of topics that vary across and within subject matter There is less self-censoring and more frankness in utterances Removes the researcher’s influence on participants’ interactions 3. Spatial and temporal comparison Archived conversations demonstrate how topics and perspective shift over time The sub-forum divide allows me to analyze how topics and perspectives shift across sub-groups of people 4. Endless research project opportunities Seemingly endless possibilities for future projects This is particularly useful for carving a long-term research agenda
  23. 23. Methodological Opportunities 1. Innovative Access  accessing hidden or scattered communities 2. Conversation candidness Participants openly discuss a variety of topics that vary across and within subject matter There is less self-censoring and more frankness in utterances Removes the researcher’s influence on participants’ interactions 3. Spatial and temporal comparison Archived conversations demonstrate how topics and perspective shift over time The sub-forum divide allows me to analyze how topics and perspectives shift across sub-groups of people 4. Endless research project opportunities Seemingly endless possibilities for future projects This is particularly useful for carving a long-term research agenda
  24. 24. Methodological Opportunities 1. Innovative Access  accessing hidden or scattered communities 2. Conversation candidness Participants openly discuss a variety of topics that vary across and within subject matter There is less self-censoring and more frankness in utterances Removes the researcher’s influence on participants’ interactions 3. Spatial and temporal comparison Archived conversations demonstrate how topics and perspective shift over time The sub-forum divide allows me to analyze how topics and perspectives shift across sub-groups of people 4. Endless research project opportunities Seemingly endless possibilities for future projects This is particularly useful for carving a long-term research agenda
  25. 25. Methodological Opportunities 1. Innovative Access  accessing hidden or scattered communities 2. Conversation candidness Participants openly discuss a variety of topics that vary across and within subject matter There is less self-censoring and more frankness in utterances Removes the researcher’s influence on participants’ interactions 3. Spatial and temporal comparison Archived conversations demonstrate how topics and perspective shift over time The sub-forum divide allows me to analyze how topics and perspectives shift across sub-groups of people 4. Endless research project opportunities Seemingly endless possibilities for future projects This is particularly useful for carving a long-term research agenda
  26. 26. Methodological Opportunities 1. Innovative Access  accessing hidden or scattered communities 2. Conversation candidness Participants openly discuss a variety of topics that vary across and within subject matter There is less self-censoring and more frankness in utterances Removes the researcher’s influence on participants’ interactions 3. Spatial and temporal comparison Archived conversations demonstrate how topics and perspective shift over time The sub-forum divide allows me to analyze how topics and perspectives shift across sub-groups of people 4. Endless research project opportunities Seemingly endless possibilities for future projects This is particularly useful for carving a long-term research agenda
  27. 27. Methodological Opportunities 1. Innovative Access  accessing hidden or scattered communities 2. Conversation candidness Participants openly discuss a variety of topics that vary across and within subject matter There is less self-censoring and more frankness in utterances Removes the researcher’s influence on participants’ interactions 3. Spatial and temporal comparison Archived conversations demonstrate how topics and perspective shift over time The sub-forum divide allows me to analyze how topics and perspectives shift across sub-groups of people 4. Endless research project opportunities Seemingly endless possibilities for future projects This is particularly useful for carving a long-term research agenda
  28. 28. Methodological Opportunities 1. Innovative Access  accessing hidden or scattered communities 2. Conversation candidness Participants openly discuss a variety of topics that vary across and within subject matter There is less self-censoring and more frankness in utterances Removes the researcher’s influence on participants’ interactions 3. Spatial and temporal comparison Archived conversations demonstrate how topics and perspective shift over time The sub-forum divide allows me to analyze how topics and perspectives shift across sub-groups of people 4. Endless research project opportunities Seemingly endless possibilities for future projects This is particularly useful for carving a long-term research agenda
  29. 29. Methodological Opportunities 1. Innovative Access  accessing hidden or scattered communities 2. Conversation candidness Participants openly discuss a variety of topics that vary across and within subject matter There is less self-censoring and more frankness in utterances Removes the researcher’s influence on participants’ interactions 3. Spatial and temporal comparison Archived conversations demonstrate how topics and perspective shift over time The sub-forum divide allows me to analyze how topics and perspectives shift across sub-groups of people 4. Endless research project opportunities Seemingly endless possibilities for future projects This is particularly useful for carving a long-term research agenda
  30. 30. Methodological Opportunities 1. Innovative Access  accessing hidden or scattered communities 2. Conversation candidness Participants openly discuss a variety of topics that vary across and within subject matter There is less self-censoring and more frankness in utterances Removes the researcher’s influence on participants’ interactions 3. Spatial and temporal comparison Archived conversations demonstrate how topics and perspective shift over time The sub-forum divide allows me to analyze how topics and perspectives shift across sub-groups of people 4. Endless research project opportunities Seemingly endless possibilities for future projects This is particularly useful for carving a long-term research agenda
  31. 31. Methodological Opportunities 1. Innovative Access  accessing hidden or scattered communities 2. Conversation candidness Participants openly discuss a variety of topics that vary across and within subject matter There is less self-censoring and more frankness in utterances Removes the researcher’s influence on participants’ interactions 3. Spatial and temporal comparison Archived conversations demonstrate how topics and perspective shift over time The sub-forum divide allows me to analyze how topics and perspectives shift across sub-groups of people 4. Endless research project opportunities Seemingly endless possibilities for future projects This is particularly useful for carving a long-term research agenda
  32. 32. Methodological Opportunities 1. Innovative Access  accessing hidden or scattered communities 2. Conversation candidness Participants openly discuss a variety of topics that vary across and within subject matter There is less self-censoring and more frankness in utterances Removes the researcher’s influence on participants’ interactions 3. Spatial and temporal comparison Archived conversations demonstrate how topics and perspective shift over time The sub-forum divide allows me to analyze how topics and perspectives shift across sub-groups of people 4. Endless research project opportunities Seemingly endless possibilities for future projects This is particularly useful for carving a long-term research agenda
  33. 33. Methodological Challenges (and Suggestions) 1. Data management (collecting, cleaning, and analyzing) Suggestions: Python Computer language has many excellent packages for collecting, cleaning, and analyzing data. It also handles large amounts of data well. 2. Programming and sampling logistics Suggestions: For programming, I practice strategic learning using google, codeacademy, YouTube, etc. For sampling, I use a mix of qualitative and quantitative content analysis in conjunction with python’s sampling module 3. Copyright and permissions issues Suggestions: First, know your site (and read the Privacy and Terms of Service statements very carefully). Next, know the law and exactly what you are asking for. Finally, learn the Fair Use Act and where to get a bit of inexpensive legal advice. 4. IRB issues and ethical considerations Suggestions: Consider your site’s access, and what kind of interaction you plan on having with posters. The more open the site and less interaction with subjects you have, the more IRB will consider the data text rather than human subjects’ research. Pseudonyms for site and users are a personal consideration, if IRB finds you exempt.
  34. 34. Methodological Challenges (and Suggestions) 1. Data management (collecting, cleaning, and analyzing) Suggestions: Python Computer language has many excellent packages for collecting, cleaning, and analyzing data. It also handles large amounts of data well. 2. Programming and sampling logistics Suggestions: For programming, I practice strategic learning using google, codeacademy, YouTube, etc. For sampling, I use a mix of qualitative and quantitative content analysis in conjunction with python’s sampling module 3. Copyright and permissions issues Suggestions: First, know your site (and read the Privacy and Terms of Service statements very carefully). Next, know the law and exactly what you are asking for. Finally, learn the Fair Use Act and where to get a bit of inexpensive legal advice. 4. IRB issues and ethical considerations Suggestions: Consider your site’s access, and what kind of interaction you plan on having with posters. The more open the site and less interaction with subjects you have, the more IRB will consider the data text rather than human subjects’ research. Pseudonyms for site and users are a personal consideration, if IRB finds you exempt.
  35. 35. Methodological Challenges (and Suggestions) 1. Data management (collecting, cleaning, and analyzing) Suggestions: Python Computer language has many excellent packages for collecting, cleaning, and analyzing data. It also handles large amounts of data well. 2. Programming and sampling logistics Suggestions: For programming, I practice strategic learning using google, codeacademy, YouTube, etc. For sampling, I use a mix of qualitative and quantitative content analysis in conjunction with python’s sampling module 3. Copyright and permissions issues Suggestions: First, know your site (and read the Privacy and Terms of Service statements very carefully). Next, know the law and exactly what you are asking for. Finally, learn the Fair Use Act and where to get a bit of inexpensive legal advice. 4. IRB issues and ethical considerations Suggestions: Consider your site’s access, and what kind of interaction you plan on having with posters. The more open the site and less interaction with subjects you have, the more IRB will consider the data text rather than human subjects’ research. Pseudonyms for site and users are a personal consideration, if IRB finds you exempt.
  36. 36. Methodological Challenges (and Suggestions) 1. Data management (collecting, cleaning, and analyzing) Suggestions: Python Computer language has many excellent packages for collecting, cleaning, and analyzing data. It also handles large amounts of data well. 2. Programming and sampling logistics Suggestions: For programming, I practice strategic learning using google, codeacademy, YouTube, etc. For sampling, I use a mix of qualitative and quantitative content analysis in conjunction with python’s sampling module 3. Copyright and permissions issues Suggestions: First, know your site (and read the Privacy and Terms of Service statements very carefully). Next, know the law and exactly what you are asking for. Finally, learn the Fair Use Act and where to get a bit of inexpensive legal advice. 4. IRB issues and ethical considerations Suggestions: Consider your site’s access, and what kind of interaction you plan on having with posters. The more open the site and less interaction with subjects you have, the more IRB will consider the data text rather than human subjects’ research. Pseudonyms for site and users are a personal consideration, if IRB finds you exempt.
  37. 37. Methodological Challenges (and Suggestions) 1. Data management (collecting, cleaning, and analyzing) Suggestions: Python Computer language has many excellent packages for collecting, cleaning, and analyzing data. It also handles large amounts of data well. 2. Programming and sampling logistics Suggestions: For programming, I practice strategic learning using google, codeacademy, YouTube, etc. For sampling, I use a mix of qualitative and quantitative content analysis in conjunction with python’s sampling module 3. Copyright and permissions issues Suggestions: First, know your site (and read the Privacy and Terms of Service statements very carefully). Next, know the law and exactly what you are asking for. Finally, learn the Fair Use Act and where to get a bit of inexpensive legal advice. 4. IRB issues and ethical considerations Suggestions: Consider your site’s access, and what kind of interaction you plan on having with posters. The more open the site and less interaction with subjects you have, the more IRB will consider the data text rather than human subjects’ research. Pseudonyms for site and users are a personal consideration, if IRB finds you exempt.
  38. 38. Methodological Challenges (and Suggestions) 1. Data management (collecting, cleaning, and analyzing) Suggestions: Python Computer language has many excellent packages for collecting, cleaning, and analyzing data. It also handles large amounts of data well. 2. Programming and sampling logistics Suggestions: For programming, I practice strategic learning using google, codeacademy, YouTube, etc. For sampling, I use a mix of qualitative and quantitative content analysis in conjunction with python’s sampling module 3. Copyright and permissions issues Suggestions: First, know your site (and read the Privacy and Terms of Service statements very carefully). Next, know the law and exactly what you are asking for. Finally, learn the Fair Use Act and where to get a bit of inexpensive legal advice. 4. IRB issues and ethical considerations Suggestions: Consider your site’s access, and what kind of interaction you plan on having with posters. The more open the site and less interaction with subjects you have, the more IRB will consider the data text rather than human subjects’ research. Pseudonyms for site and users are a personal consideration, if IRB finds you exempt.
  39. 39. Methodological Challenges (and Suggestions) 1. Data management (collecting, cleaning, and analyzing) Suggestions: Python Computer language has many excellent packages for collecting, cleaning, and analyzing data. It also handles large amounts of data well. 2. Programming and sampling logistics Suggestions: For programming, I practice strategic learning using google, codeacademy, YouTube, etc. For sampling, I use a mix of qualitative and quantitative content analysis in conjunction with python’s sampling module 3. Copyright and permissions issues Suggestions: First, know your site (and read the Privacy and Terms of Service statements very carefully). Next, know the law and exactly what you are asking for. Finally, learn the Fair Use Act and where to get a bit of inexpensive legal advice. 4. IRB issues and ethical considerations Suggestions: Consider your site’s access, and what kind of interaction you plan on having with posters. The more open the site and less interaction with subjects you have, the more IRB will consider the data text rather than human subjects’ research. Pseudonyms for site and users are a personal consideration, if IRB finds you exempt.
  40. 40. Methodological Challenges (and Suggestions) 1. Data management (collecting, cleaning, and analyzing) Suggestions: Python Computer language has many excellent packages for collecting, cleaning, and analyzing data. It also handles large amounts of data well. 2. Programming and sampling logistics Suggestions: For programming, I practice strategic learning using google, codeacademy, YouTube, etc. For sampling, I use a mix of qualitative and quantitative content analysis in conjunction with python’s sampling module 3. Copyright and permissions issues Suggestions: First, know your site (and read the Privacy and Terms of Service statements very carefully). Next, know the law and exactly what you are asking for. Finally, learn the Fair Use Act and where to get a bit of inexpensive legal advice. 4. IRB issues and ethical considerations Suggestions: Consider your site’s access, and what kind of interaction you plan on having with posters. The more open the site and less interaction with subjects you have, the more IRB will consider the data text rather than human subjects’ research. Pseudonyms for site and users are a personal consideration, if IRB finds you exempt.
  41. 41. Methodological Challenges (and Suggestions) 1. Data management (collecting, cleaning, and analyzing) Suggestions: Python Computer language has many excellent packages for collecting, cleaning, and analyzing data. It also handles large amounts of data well. 2. Programming and sampling logistics Suggestions: For programming, I practice strategic learning using google, codeacademy, YouTube, etc. For sampling, I use a mix of qualitative and quantitative content analysis in conjunction with python’s sampling module 3. Copyright and permissions issues Suggestions: First, know your site (and read the Privacy and Terms of Service statements very carefully). Next, know the law and exactly what you are asking for. Finally, learn the Fair Use Act and where to get a bit of inexpensive legal advice. 4. IRB issues and ethical considerations Suggestions: Consider your site’s access, and what kind of interaction you plan on having with posters. The more open the site and less interaction with subjects you have, the more IRB will consider the data text rather than human subjects’ research. Pseudonyms for site and users are a personal consideration, if IRB finds you exempt.
  42. 42. Thank you

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