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E-raamat: Data for Journalists: A Practical Guide for Computer-Assisted Reporting

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(University of Illinois at Urbana-Champaign, USA)
  • Formaat: 252 pages
  • Ilmumisaeg: 17-Dec-2018
  • Kirjastus: Routledge
  • Keel: eng
  • ISBN-13: 9781351249294
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Data for Journalists: A Practical Guide for Computer-Assisted ReportingSuurem pilt
  • Formaat: 252 pages
  • Ilmumisaeg: 17-Dec-2018
  • Kirjastus: Routledge
  • Keel: eng
  • ISBN-13: 9781351249294
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This straightforward and effective how-to guide provides the basics for any reporter or journalism student beginning to use data for news stories. It has step-by-step instructions on how to do basic data analysis in journalism while addressing why these digital tools should be an integral part of reporting in the 21st century. In an ideal core text for courses on data-driven journalism or computer-assisted reporting, Houston emphasizes that journalists are accountable for the accuracy and relevance of the data they acquire and share.

With a refreshed design, this updated new edition includes expanded coverage on social media, scraping data from the web, and text-mining, and provides journalists with the tips and tools they need for working with data.
List of Boxes
xi
Preface xiii
Features xv
New to This Edition xvii
Acknowledgments xix
1 What Data Journalism and Computer-Assisted Reporting Is and Why Journalists Use It
1(18)
The Fundamentals Remain
2(9)
How to Learn: Trial and Error---and Repetition
11(1)
Where You Are Going
11(3)
A Final Thought
14(1)
Chapter Summary
15(1)
Applying CAR
15(1)
Suggested Exercises
16(3)
Part I Learning Computer-Assisted Reporting Skills
2 Online Resources: Researching and Finding Data on the Internet
19(24)
Finding Data
21(2)
Digital Information and Data on the Internet
23(1)
Using Online Resources
23(1)
What Online Resources to Use
24(1)
Digital Library Researchers and Journalists
25(1)
Newsroom Databases
25(1)
Discussion Groups and Social Media
25(1)
Using Boolean Logic to Search the Internet
26(1)
Downloading Databases
27(2)
Downloading Different Files
29(8)
Web Scraping
37(2)
Chapter Summary
39(1)
Applying CAR
40(1)
Suggested Exercises
41(2)
3 Gathering and Analyzing Text and Social Media
43(16)
Social Media for News Gathering and Analysis
50(6)
Crowd-Sourcing
56(1)
Authenticity and Accuracy
57(1)
Chapter Summary
57(1)
Applying CAR
57(1)
Suggested Exercises
58(1)
4 Spreadsheets, Part 1: Basic Math for Journalists
59(20)
Becoming Friendly with Numbers
60(2)
Learning Addresses
62(2)
Calculating Percentages
64(3)
Going from Horizontal to Vertical
67(2)
Comparing Parts to the Sum
69(2)
Sorting the Results
71(3)
Using Average and Median for Better Accuracy
74(2)
Interpreting Outliers
76(1)
Chapter Summary
77(1)
Applying CAR
77(1)
Suggested Exercises
78(1)
5 Spreadsheets, Part 2: More Math that Matters
79(24)
Rates
80(4)
Ranking
84(2)
Filtering
86(3)
Ratios
89(1)
Pivot Tables
90(7)
Graphs and Charts
97(3)
Chapter Summary
100(1)
Applying CAR
100(1)
Suggested Exercises
101(2)
6 Database Managers, Part 1: Searching and Summarizing
103(20)
The Query
109(3)
Selecting and Searching
112(1)
Criteria and Filtering
113(1)
Sorting
114(1)
Criteria and Wildcards
114(2)
Boolean Logic: And, Or, Not
116(2)
Grouping
118(3)
Chapter Summary
121(1)
Applying CAR
121(1)
Suggested Exercises
122(1)
7 Database Managers, Part 2: Matchmaking
123(12)
Relational Databases Are Everywhere
124(1)
Joining Tables
125(2)
Enterprise Matchmaking
127(4)
Chapter Summary
131(1)
Applying CAR
132(1)
Suggested Exercises
132(3)
Part II Using Computer-Assisted Reporting in News Stories
8 Getting Data Not on the Web: How to Find and Negotiate for Data
135(14)
Finding Data
136(3)
Obtaining a Database
139(1)
The Record Layout
140(2)
Privacy and Security Issues
142(1)
High Costs
143(1)
Importing
144(2)
Chapter Summary
146(1)
Applying CAR
146(1)
Suggested Exercises
147(2)
9 Building Your Own Database: How to Develop Exclusive Sources
149(12)
When to Build
152(1)
Spreadsheet or Database Manager
153(1)
Using the Database Manager
154(2)
Creating a Relational Database
156(2)
Chapter Summary
158(1)
Applying CAR
158(1)
Suggested Exercises
159(2)
10 Dirty Data: How to Fact Check Your Data and Clean It
161(18)
Never Trust the Data
163(2)
Two Rules
165(1)
Record Layout
166(1)
Record Layout Miscues
166(2)
Cryptic Codes
168(2)
Sorry, Wrong Number
170(1)
Where Is the Standard?
171(2)
Header-Aches
173(2)
Numbers Versus Text
175(1)
Offensive Characters
175(1)
Chapter Summary
176(1)
Applying CAR
177(1)
Suggested Exercises
177(2)
11 Doing the Data Journalism and Computer-Assisted Reporting Story: How to Report and Write with Data
179(14)
Pick a Story You Know Can Be Done
180(1)
Pick a Database You Can Get
181(1)
Some First-Time Examples
181(1)
Start Small
182(1)
Building Your Own
183(1)
Match the Database to Your Knowledge
183(1)
The Minimum Story
184(1)
Keep Up with Other Reporters' Work
185(1)
Integrate Databases into Your Daily Work
185(1)
Find a Partner
186(1)
Become Familiar with the Field of Data Programming
186(1)
Look for Tips
186(1)
Writing the Story
187(1)
Good Reporting and Ethics
188(1)
Stay Curious, Get Excited
188(2)
Chapter Summary
190(1)
Applying CAR
190(1)
Suggested Exercises
191(2)
Appendix A A Short Introduction to Mapping Data 193(12)
Appendix B A Short Introduction to Social Network Analysis 205(10)
Selected Bibliography 215(2)
Websites 217(2)
Sources for Key Examples 219(2)
Glossary 221(4)
Index 225
Brant Houston is a Professor and the Knight Chair in Investigative Reporting at the University of Illinois, where he teaches journalism and oversees an online newsroom. An award-winning journalist, he was an investigative reporter at U.S. newspapers for 17 years. For more than a decade, he served as executive director of Investigative Reporters and Editors, a now 6,000-member association headquartered at the University of Missouri School of Journalism, where he also taught investigative and data reporting. Houston has conducted more than 400 seminars for professional journalists and students in 30 countries, and he is a co-founder of networks of nonprofit newsrooms and educators throughout the world.
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