SlideShare a Scribd company logo
1 of 30
GEOG 420 / POL 420 / SOC 420
Spring 2018
 Examples: Documents, reports, manuscripts,
memoirs, speeches, etc.
 Issue ofTime (History) and Space (Location)
 Fewer ethical issues than observation,
interviewing, etc.
ADVANTAGES
 Access difficult subjects
 Raw data is nonreactive
 Analysis over time
 Increased sample size
 Cost
DISADVANTAGES
 Selective Survival
 Incomplete Nature
 Biased Content
 Unavailability of Records
 Lack of Standard Format
 Records NOT part of organized or systematic
record-keeping program.
 Produced and preserved in a casual, personal,
and sometimes accidental manner
 Examples: Diaries, memoirs, manuscripts,
correspondence, autobiographies,
“media of temporary existence”
(e.g. brochures, posters, etc.)
 Produced by organizations
 Carefully stored, easily accessed, and
available for long periods of time
 Examples: OpenSecrets,THOMAS, Almanac
of American Politics, University Crime Log
 Advantages
 Cost –Time and Money
 Accessibility
 More Extensive
 Disadvantages
 Control of record-keeping organization
 Unwillingness of organization to share data
 Finding out record-keeping organization’s practices
 How do we actually analyze the data that we collect?
 Step #1: Materials to Include in Analysis
 Selection guided by theory and existing research
 Examples:
 Speeches, newspapers, blogs, magazines, etc.
 Materials collectively make up sampling frame
 Step 2: Define Recording or Coding Units
 Units that are distinguished for description,
recording, and coding purposes in analysis
 Examples:
 Word or sentence fragment
 Sentence
 Paragraph
 Story
 Item asWhole
 Step 3: Categories of Content to Measure
 Variables that you want to focus on in study
 Can be most important part of content analysis
 Example: Viewing nightly news programs and
coding stories based on specific issues
(economy, health care, crime, education, etc.)
 Step 4: Devise System to Measure Content
 Presence or absence of given content category
VALIDITY
 Precise explanations of
procedures and categories
RELIABILITY
 Demonstrated through
intercoder reliability
 Two or more analysis,
using same procedures and
definitions, agree on
content categories
applied to material
 Reading
 Human Coding / Manual Content Analysis
 Dictionary-Based Approaches
 Supervised Learning
 Analysis process involves reading a text
 Advantages:
 Fundamental for inferring meaning from text
 Fewer assumptions that other methods
 Disadvantage: Cost
 Standard methodology for content analysis
and text coding with social science research
 Coders read text and attempt to assign one
of a set of categories to each unit
ADVANTAGES
 Less substantive
knowledge than deep
reading of the texts
 Less costly than reading
DISADVANTAGES
 Higher initial costs
 Arriving at categorization
scheme requires knowledge
of subject matter and
substantial time
 Analyst develops list of words and phrases
likely to be in a particular category
 Examples: LIWC, DICTION, JFREQ
 Computer tallies words in given categories
ADVANTAGES
 Analysis Costs
 Large number of texts
can be processed quickly
 Descriptive numerical
summaries are easily
generated
DISADVANTAGES
 High startup costs
 Building appropriate
dictionary requires good
deal of knowledge
 Trial and error
 Hand coding done to subset of texts
 “Training” Set: Evaluation tool for “test” set
 Algorithms used to attempt to infer mapping
from text features to hand-coded categories in
training set
ADVANTAGES
 Large amount of texts
due to automated process
DISADVANTAGES
 High startup costs due to
human construction of
“training” and “test” sets
of documents

More Related Content

What's hot

Research Literacy GEDU6170 MSVU
Research Literacy GEDU6170 MSVUResearch Literacy GEDU6170 MSVU
Research Literacy GEDU6170 MSVUSaad Chahine
 
RDAP 15 Data Management Outreach for the Humanities: A University of Illinois...
RDAP 15 Data Management Outreach for the Humanities: A University of Illinois...RDAP 15 Data Management Outreach for the Humanities: A University of Illinois...
RDAP 15 Data Management Outreach for the Humanities: A University of Illinois...ASIS&T
 
Longer research paper by parsu ram karkee
Longer research paper by parsu ram karkeeLonger research paper by parsu ram karkee
Longer research paper by parsu ram karkeePreritKarki
 
Natural Language Processing in the Wild.pptx
Natural Language Processing in the Wild.pptxNatural Language Processing in the Wild.pptx
Natural Language Processing in the Wild.pptxColleen Farrelly
 
Privacy in Research Data Managemnt - Use Cases
Privacy in Research Data Managemnt - Use CasesPrivacy in Research Data Managemnt - Use Cases
Privacy in Research Data Managemnt - Use CasesMicah Altman
 
Academic library orientation for all
Academic library orientation for allAcademic library orientation for all
Academic library orientation for allEvelyn Weinberger
 
Monday presentation
Monday presentationMonday presentation
Monday presentationAhmadu Bello
 
Teaching computer assisted reporting in 2015, Brant Houston #gijc15
Teaching computer assisted reporting in 2015, Brant Houston #gijc15Teaching computer assisted reporting in 2015, Brant Houston #gijc15
Teaching computer assisted reporting in 2015, Brant Houston #gijc15gijn
 
Relevance vs Subject
Relevance vs SubjectRelevance vs Subject
Relevance vs SubjectDavidPixton
 
Library resources and services for grant development
Library resources and services for grant developmentLibrary resources and services for grant development
Library resources and services for grant developmentrds-wayne-edu
 
Relevance vs Info Needs
Relevance vs Info NeedsRelevance vs Info Needs
Relevance vs Info NeedsDavidPixton
 
Metadata Quality
Metadata QualityMetadata Quality
Metadata Qualitytbruce
 
Resource sharing opportunities among academic libraries
Resource sharing opportunities among academic librariesResource sharing opportunities among academic libraries
Resource sharing opportunities among academic librariesKhalid Mahmood
 
Relevance vs Utility
Relevance vs UtilityRelevance vs Utility
Relevance vs UtilityDavidPixton
 

What's hot (20)

Research Literacy GEDU6170 MSVU
Research Literacy GEDU6170 MSVUResearch Literacy GEDU6170 MSVU
Research Literacy GEDU6170 MSVU
 
Beyond Google
Beyond Google Beyond Google
Beyond Google
 
Care Research Dissemination Guide
Care Research Dissemination GuideCare Research Dissemination Guide
Care Research Dissemination Guide
 
HD Judge Training 2011
HD Judge Training 2011HD Judge Training 2011
HD Judge Training 2011
 
RDAP 15 Data Management Outreach for the Humanities: A University of Illinois...
RDAP 15 Data Management Outreach for the Humanities: A University of Illinois...RDAP 15 Data Management Outreach for the Humanities: A University of Illinois...
RDAP 15 Data Management Outreach for the Humanities: A University of Illinois...
 
Longer research paper by parsu ram karkee
Longer research paper by parsu ram karkeeLonger research paper by parsu ram karkee
Longer research paper by parsu ram karkee
 
Natural Language Processing in the Wild.pptx
Natural Language Processing in the Wild.pptxNatural Language Processing in the Wild.pptx
Natural Language Processing in the Wild.pptx
 
Privacy in Research Data Managemnt - Use Cases
Privacy in Research Data Managemnt - Use CasesPrivacy in Research Data Managemnt - Use Cases
Privacy in Research Data Managemnt - Use Cases
 
Careers in Science and Technology Policy
Careers in Science and Technology PolicyCareers in Science and Technology Policy
Careers in Science and Technology Policy
 
Academic library orientation for all
Academic library orientation for allAcademic library orientation for all
Academic library orientation for all
 
Monday presentation
Monday presentationMonday presentation
Monday presentation
 
Research workshop
Research workshopResearch workshop
Research workshop
 
Teaching computer assisted reporting in 2015, Brant Houston #gijc15
Teaching computer assisted reporting in 2015, Brant Houston #gijc15Teaching computer assisted reporting in 2015, Brant Houston #gijc15
Teaching computer assisted reporting in 2015, Brant Houston #gijc15
 
Relevance vs Subject
Relevance vs SubjectRelevance vs Subject
Relevance vs Subject
 
Library resources and services for grant development
Library resources and services for grant developmentLibrary resources and services for grant development
Library resources and services for grant development
 
Advanced search topics
Advanced search topicsAdvanced search topics
Advanced search topics
 
Relevance vs Info Needs
Relevance vs Info NeedsRelevance vs Info Needs
Relevance vs Info Needs
 
Metadata Quality
Metadata QualityMetadata Quality
Metadata Quality
 
Resource sharing opportunities among academic libraries
Resource sharing opportunities among academic librariesResource sharing opportunities among academic libraries
Resource sharing opportunities among academic libraries
 
Relevance vs Utility
Relevance vs UtilityRelevance vs Utility
Relevance vs Utility
 

Similar to Content Analysis

Content analysis
Content analysisContent analysis
Content analysisatrantham
 
The Process of Qualitative Research Methods
The Process of Qualitative Research MethodsThe Process of Qualitative Research Methods
The Process of Qualitative Research Methodsevamaealvarado
 
Jemimah qualitative data collection
Jemimah qualitative data collectionJemimah qualitative data collection
Jemimah qualitative data collectiongenderassets
 
Chapters 1 And 2
Chapters 1 And 2Chapters 1 And 2
Chapters 1 And 2EDUCAUSE
 
Information Skills For Researchers V3
Information Skills For Researchers V3Information Skills For Researchers V3
Information Skills For Researchers V3Jacqueline Thomas
 
615900072
615900072615900072
615900072picktru
 
Data Management in Legal Research: Data Organisation and Analysis
Data Management in Legal Research: Data Organisation and AnalysisData Management in Legal Research: Data Organisation and Analysis
Data Management in Legal Research: Data Organisation and AnalysisPreeti Sikder
 
Data collection methods in Nursing research
Data collection methods in Nursing researchData collection methods in Nursing research
Data collection methods in Nursing researchDeepa Ajithkumar
 
20110428 ARMA Amarillo Inventory Your Electronic Records
20110428 ARMA Amarillo Inventory Your Electronic Records20110428 ARMA Amarillo Inventory Your Electronic Records
20110428 ARMA Amarillo Inventory Your Electronic RecordsJesse Wilkins
 
DATA COLLECTION METHODS PRESENTATION ( EMMANUEL SIAW OKAI).pdf
DATA COLLECTION METHODS  PRESENTATION ( EMMANUEL SIAW OKAI).pdfDATA COLLECTION METHODS  PRESENTATION ( EMMANUEL SIAW OKAI).pdf
DATA COLLECTION METHODS PRESENTATION ( EMMANUEL SIAW OKAI).pdfemmanuelsokai
 
Unit 4 Student Guide
Unit 4 Student GuideUnit 4 Student Guide
Unit 4 Student Guidetotal
 

Similar to Content Analysis (20)

Content analysis
Content analysisContent analysis
Content analysis
 
The Process of Qualitative Research Methods
The Process of Qualitative Research MethodsThe Process of Qualitative Research Methods
The Process of Qualitative Research Methods
 
Jemimah qualitative data collection
Jemimah qualitative data collectionJemimah qualitative data collection
Jemimah qualitative data collection
 
Chapters 1 And 2
Chapters 1 And 2Chapters 1 And 2
Chapters 1 And 2
 
Field research
Field researchField research
Field research
 
Information Skills For Researchers V3
Information Skills For Researchers V3Information Skills For Researchers V3
Information Skills For Researchers V3
 
Field research
Field researchField research
Field research
 
615900072
615900072615900072
615900072
 
IRP for Dummies
IRP for DummiesIRP for Dummies
IRP for Dummies
 
Data Management in Legal Research: Data Organisation and Analysis
Data Management in Legal Research: Data Organisation and AnalysisData Management in Legal Research: Data Organisation and Analysis
Data Management in Legal Research: Data Organisation and Analysis
 
QUALITATIVE DATA ANALYSIS.ppt
QUALITATIVE DATA ANALYSIS.pptQUALITATIVE DATA ANALYSIS.ppt
QUALITATIVE DATA ANALYSIS.ppt
 
Data collection methods in Nursing research
Data collection methods in Nursing researchData collection methods in Nursing research
Data collection methods in Nursing research
 
20110428 ARMA Amarillo Inventory Your Electronic Records
20110428 ARMA Amarillo Inventory Your Electronic Records20110428 ARMA Amarillo Inventory Your Electronic Records
20110428 ARMA Amarillo Inventory Your Electronic Records
 
DATA COLLECTION METHODS PRESENTATION ( EMMANUEL SIAW OKAI).pdf
DATA COLLECTION METHODS  PRESENTATION ( EMMANUEL SIAW OKAI).pdfDATA COLLECTION METHODS  PRESENTATION ( EMMANUEL SIAW OKAI).pdf
DATA COLLECTION METHODS PRESENTATION ( EMMANUEL SIAW OKAI).pdf
 
Qualitative data analysis
Qualitative data analysisQualitative data analysis
Qualitative data analysis
 
Qualitative Research
Qualitative ResearchQualitative Research
Qualitative Research
 
Qualitative Research
Qualitative ResearchQualitative Research
Qualitative Research
 
Trm Planets Training Pp Module
Trm Planets Training Pp ModuleTrm Planets Training Pp Module
Trm Planets Training Pp Module
 
Unit 4 Student Guide
Unit 4 Student GuideUnit 4 Student Guide
Unit 4 Student Guide
 
SOC2002 Lecture 2
SOC2002 Lecture 2SOC2002 Lecture 2
SOC2002 Lecture 2
 

More from atrantham

PPOL 511 Course Introduction
PPOL 511 Course IntroductionPPOL 511 Course Introduction
PPOL 511 Course Introductionatrantham
 
Financial Scandals
Financial ScandalsFinancial Scandals
Financial Scandalsatrantham
 
More Sex Scandals
More Sex ScandalsMore Sex Scandals
More Sex Scandalsatrantham
 
Clinton and Lewinsky
Clinton and LewinskyClinton and Lewinsky
Clinton and Lewinskyatrantham
 
Plunkitt of Tammany Hall
Plunkitt of Tammany HallPlunkitt of Tammany Hall
Plunkitt of Tammany Hallatrantham
 
Political Machines
Political MachinesPolitical Machines
Political Machinesatrantham
 
State Legislatures
State LegislaturesState Legislatures
State Legislaturesatrantham
 
Governors and Executives
Governors and ExecutivesGovernors and Executives
Governors and Executivesatrantham
 
State Legislatures
State LegislaturesState Legislatures
State Legislaturesatrantham
 
Political Parties and Interest Groups
Political Parties and Interest GroupsPolitical Parties and Interest Groups
Political Parties and Interest Groupsatrantham
 
Political Attitudes and Participation
Political Attitudes and ParticipationPolitical Attitudes and Participation
Political Attitudes and Participationatrantham
 
Civil Rights
Civil RightsCivil Rights
Civil Rightsatrantham
 
Civil Liberties
Civil LibertiesCivil Liberties
Civil Libertiesatrantham
 
POL 375 Trust Legitimacy Support for Government
POL 375 Trust Legitimacy Support for GovernmentPOL 375 Trust Legitimacy Support for Government
POL 375 Trust Legitimacy Support for Governmentatrantham
 
Pol 375 Defining Scandal and Corruption
Pol 375 Defining Scandal and CorruptionPol 375 Defining Scandal and Corruption
Pol 375 Defining Scandal and Corruptionatrantham
 
POL 318 State Consitutions
POL 318 State ConsitutionsPOL 318 State Consitutions
POL 318 State Consitutionsatrantham
 
POL 318 Federalism
POL 318 FederalismPOL 318 Federalism
POL 318 Federalismatrantham
 

More from atrantham (20)

PPOL 511 Course Introduction
PPOL 511 Course IntroductionPPOL 511 Course Introduction
PPOL 511 Course Introduction
 
Financial Scandals
Financial ScandalsFinancial Scandals
Financial Scandals
 
Bureaucracy
BureaucracyBureaucracy
Bureaucracy
 
More Sex Scandals
More Sex ScandalsMore Sex Scandals
More Sex Scandals
 
Clinton and Lewinsky
Clinton and LewinskyClinton and Lewinsky
Clinton and Lewinsky
 
Plunkitt of Tammany Hall
Plunkitt of Tammany HallPlunkitt of Tammany Hall
Plunkitt of Tammany Hall
 
Political Machines
Political MachinesPolitical Machines
Political Machines
 
State Legislatures
State LegislaturesState Legislatures
State Legislatures
 
Governors and Executives
Governors and ExecutivesGovernors and Executives
Governors and Executives
 
State Legislatures
State LegislaturesState Legislatures
State Legislatures
 
Political Parties and Interest Groups
Political Parties and Interest GroupsPolitical Parties and Interest Groups
Political Parties and Interest Groups
 
Political Attitudes and Participation
Political Attitudes and ParticipationPolitical Attitudes and Participation
Political Attitudes and Participation
 
Presidency
Presidency Presidency
Presidency
 
Congress
CongressCongress
Congress
 
Civil Rights
Civil RightsCivil Rights
Civil Rights
 
Civil Liberties
Civil LibertiesCivil Liberties
Civil Liberties
 
POL 375 Trust Legitimacy Support for Government
POL 375 Trust Legitimacy Support for GovernmentPOL 375 Trust Legitimacy Support for Government
POL 375 Trust Legitimacy Support for Government
 
Pol 375 Defining Scandal and Corruption
Pol 375 Defining Scandal and CorruptionPol 375 Defining Scandal and Corruption
Pol 375 Defining Scandal and Corruption
 
POL 318 State Consitutions
POL 318 State ConsitutionsPOL 318 State Consitutions
POL 318 State Consitutions
 
POL 318 Federalism
POL 318 FederalismPOL 318 Federalism
POL 318 Federalism
 

Recently uploaded

Employee wellbeing at the workplace.pptx
Employee wellbeing at the workplace.pptxEmployee wellbeing at the workplace.pptx
Employee wellbeing at the workplace.pptxNirmalaLoungPoorunde1
 
Presiding Officer Training module 2024 lok sabha elections
Presiding Officer Training module 2024 lok sabha electionsPresiding Officer Training module 2024 lok sabha elections
Presiding Officer Training module 2024 lok sabha electionsanshu789521
 
Science lesson Moon for 4th quarter lesson
Science lesson Moon for 4th quarter lessonScience lesson Moon for 4th quarter lesson
Science lesson Moon for 4th quarter lessonJericReyAuditor
 
Enzyme, Pharmaceutical Aids, Miscellaneous Last Part of Chapter no 5th.pdf
Enzyme, Pharmaceutical Aids, Miscellaneous Last Part of Chapter no 5th.pdfEnzyme, Pharmaceutical Aids, Miscellaneous Last Part of Chapter no 5th.pdf
Enzyme, Pharmaceutical Aids, Miscellaneous Last Part of Chapter no 5th.pdfSumit Tiwari
 
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Krashi Coaching
 
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️9953056974 Low Rate Call Girls In Saket, Delhi NCR
 
How to Make a Pirate ship Primary Education.pptx
How to Make a Pirate ship Primary Education.pptxHow to Make a Pirate ship Primary Education.pptx
How to Make a Pirate ship Primary Education.pptxmanuelaromero2013
 
Mastering the Unannounced Regulatory Inspection
Mastering the Unannounced Regulatory InspectionMastering the Unannounced Regulatory Inspection
Mastering the Unannounced Regulatory InspectionSafetyChain Software
 
Introduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher EducationIntroduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher Educationpboyjonauth
 
Class 11 Legal Studies Ch-1 Concept of State .pdf
Class 11 Legal Studies Ch-1 Concept of State .pdfClass 11 Legal Studies Ch-1 Concept of State .pdf
Class 11 Legal Studies Ch-1 Concept of State .pdfakmcokerachita
 
A Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy ReformA Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy ReformChameera Dedduwage
 
Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)eniolaolutunde
 
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptxPOINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptxSayali Powar
 
Introduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxIntroduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxpboyjonauth
 
How to Configure Email Server in Odoo 17
How to Configure Email Server in Odoo 17How to Configure Email Server in Odoo 17
How to Configure Email Server in Odoo 17Celine George
 
_Math 4-Q4 Week 5.pptx Steps in Collecting Data
_Math 4-Q4 Week 5.pptx Steps in Collecting Data_Math 4-Q4 Week 5.pptx Steps in Collecting Data
_Math 4-Q4 Week 5.pptx Steps in Collecting DataJhengPantaleon
 
The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13Steve Thomason
 
18-04-UA_REPORT_MEDIALITERAСY_INDEX-DM_23-1-final-eng.pdf
18-04-UA_REPORT_MEDIALITERAСY_INDEX-DM_23-1-final-eng.pdf18-04-UA_REPORT_MEDIALITERAСY_INDEX-DM_23-1-final-eng.pdf
18-04-UA_REPORT_MEDIALITERAСY_INDEX-DM_23-1-final-eng.pdfssuser54595a
 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityGeoBlogs
 
History Class XII Ch. 3 Kinship, Caste and Class (1).pptx
History Class XII Ch. 3 Kinship, Caste and Class (1).pptxHistory Class XII Ch. 3 Kinship, Caste and Class (1).pptx
History Class XII Ch. 3 Kinship, Caste and Class (1).pptxsocialsciencegdgrohi
 

Recently uploaded (20)

Employee wellbeing at the workplace.pptx
Employee wellbeing at the workplace.pptxEmployee wellbeing at the workplace.pptx
Employee wellbeing at the workplace.pptx
 
Presiding Officer Training module 2024 lok sabha elections
Presiding Officer Training module 2024 lok sabha electionsPresiding Officer Training module 2024 lok sabha elections
Presiding Officer Training module 2024 lok sabha elections
 
Science lesson Moon for 4th quarter lesson
Science lesson Moon for 4th quarter lessonScience lesson Moon for 4th quarter lesson
Science lesson Moon for 4th quarter lesson
 
Enzyme, Pharmaceutical Aids, Miscellaneous Last Part of Chapter no 5th.pdf
Enzyme, Pharmaceutical Aids, Miscellaneous Last Part of Chapter no 5th.pdfEnzyme, Pharmaceutical Aids, Miscellaneous Last Part of Chapter no 5th.pdf
Enzyme, Pharmaceutical Aids, Miscellaneous Last Part of Chapter no 5th.pdf
 
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
 
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️
 
How to Make a Pirate ship Primary Education.pptx
How to Make a Pirate ship Primary Education.pptxHow to Make a Pirate ship Primary Education.pptx
How to Make a Pirate ship Primary Education.pptx
 
Mastering the Unannounced Regulatory Inspection
Mastering the Unannounced Regulatory InspectionMastering the Unannounced Regulatory Inspection
Mastering the Unannounced Regulatory Inspection
 
Introduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher EducationIntroduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher Education
 
Class 11 Legal Studies Ch-1 Concept of State .pdf
Class 11 Legal Studies Ch-1 Concept of State .pdfClass 11 Legal Studies Ch-1 Concept of State .pdf
Class 11 Legal Studies Ch-1 Concept of State .pdf
 
A Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy ReformA Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy Reform
 
Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)
 
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptxPOINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
 
Introduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxIntroduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptx
 
How to Configure Email Server in Odoo 17
How to Configure Email Server in Odoo 17How to Configure Email Server in Odoo 17
How to Configure Email Server in Odoo 17
 
_Math 4-Q4 Week 5.pptx Steps in Collecting Data
_Math 4-Q4 Week 5.pptx Steps in Collecting Data_Math 4-Q4 Week 5.pptx Steps in Collecting Data
_Math 4-Q4 Week 5.pptx Steps in Collecting Data
 
The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13
 
18-04-UA_REPORT_MEDIALITERAСY_INDEX-DM_23-1-final-eng.pdf
18-04-UA_REPORT_MEDIALITERAСY_INDEX-DM_23-1-final-eng.pdf18-04-UA_REPORT_MEDIALITERAСY_INDEX-DM_23-1-final-eng.pdf
18-04-UA_REPORT_MEDIALITERAСY_INDEX-DM_23-1-final-eng.pdf
 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activity
 
History Class XII Ch. 3 Kinship, Caste and Class (1).pptx
History Class XII Ch. 3 Kinship, Caste and Class (1).pptxHistory Class XII Ch. 3 Kinship, Caste and Class (1).pptx
History Class XII Ch. 3 Kinship, Caste and Class (1).pptx
 

Content Analysis

  • 1. GEOG 420 / POL 420 / SOC 420 Spring 2018
  • 2.
  • 3.
  • 4.  Examples: Documents, reports, manuscripts, memoirs, speeches, etc.  Issue ofTime (History) and Space (Location)  Fewer ethical issues than observation, interviewing, etc.
  • 5. ADVANTAGES  Access difficult subjects  Raw data is nonreactive  Analysis over time  Increased sample size  Cost DISADVANTAGES  Selective Survival  Incomplete Nature  Biased Content  Unavailability of Records  Lack of Standard Format
  • 6.
  • 7.  Records NOT part of organized or systematic record-keeping program.  Produced and preserved in a casual, personal, and sometimes accidental manner  Examples: Diaries, memoirs, manuscripts, correspondence, autobiographies, “media of temporary existence” (e.g. brochures, posters, etc.)
  • 8.
  • 9.  Produced by organizations  Carefully stored, easily accessed, and available for long periods of time  Examples: OpenSecrets,THOMAS, Almanac of American Politics, University Crime Log
  • 10.  Advantages  Cost –Time and Money  Accessibility  More Extensive  Disadvantages  Control of record-keeping organization  Unwillingness of organization to share data  Finding out record-keeping organization’s practices  How do we actually analyze the data that we collect?
  • 11.
  • 12.  Step #1: Materials to Include in Analysis  Selection guided by theory and existing research  Examples:  Speeches, newspapers, blogs, magazines, etc.  Materials collectively make up sampling frame
  • 13.  Step 2: Define Recording or Coding Units  Units that are distinguished for description, recording, and coding purposes in analysis  Examples:  Word or sentence fragment  Sentence  Paragraph  Story  Item asWhole
  • 14.  Step 3: Categories of Content to Measure  Variables that you want to focus on in study  Can be most important part of content analysis  Example: Viewing nightly news programs and coding stories based on specific issues (economy, health care, crime, education, etc.)
  • 15.  Step 4: Devise System to Measure Content  Presence or absence of given content category
  • 16.
  • 17. VALIDITY  Precise explanations of procedures and categories RELIABILITY  Demonstrated through intercoder reliability  Two or more analysis, using same procedures and definitions, agree on content categories applied to material
  • 18.
  • 19.  Reading  Human Coding / Manual Content Analysis  Dictionary-Based Approaches  Supervised Learning
  • 20.
  • 21.  Analysis process involves reading a text  Advantages:  Fundamental for inferring meaning from text  Fewer assumptions that other methods  Disadvantage: Cost
  • 22.
  • 23.  Standard methodology for content analysis and text coding with social science research  Coders read text and attempt to assign one of a set of categories to each unit
  • 24. ADVANTAGES  Less substantive knowledge than deep reading of the texts  Less costly than reading DISADVANTAGES  Higher initial costs  Arriving at categorization scheme requires knowledge of subject matter and substantial time
  • 25.
  • 26.  Analyst develops list of words and phrases likely to be in a particular category  Examples: LIWC, DICTION, JFREQ  Computer tallies words in given categories
  • 27. ADVANTAGES  Analysis Costs  Large number of texts can be processed quickly  Descriptive numerical summaries are easily generated DISADVANTAGES  High startup costs  Building appropriate dictionary requires good deal of knowledge  Trial and error
  • 28.
  • 29.  Hand coding done to subset of texts  “Training” Set: Evaluation tool for “test” set  Algorithms used to attempt to infer mapping from text features to hand-coded categories in training set
  • 30. ADVANTAGES  Large amount of texts due to automated process DISADVANTAGES  High startup costs due to human construction of “training” and “test” sets of documents