Rreth këtij libri elektronik
A guide for using computational text analysis to learn about the social world
From social media posts and text messages to digital government documents and archives, researchers are bombarded with a deluge of text reflecting the social world. This textual data gives unprecedented insights into fundamental questions in the social sciences, humanities, and industry. Meanwhile new machine learning tools are rapidly transforming the way science and business are conducted. Text as Data shows how to combine new sources of data, machine learning tools, and social science research design to develop and evaluate new insights.
Text as Data is organized around the core tasks in research projects using text—representation, discovery, measurement, prediction, and causal inference. The authors offer a sequential, iterative, and inductive approach to research design. Each research task is presented complete with real-world applications, example methods, and a distinct style of task-focused research.
Bridging many divides—computer science and social science, the qualitative and the quantitative, and industry and academia—Text as Data is an ideal resource for anyone wanting to analyze large collections of text in an era when data is abundant and computation is cheap, but the enduring challenges of social science remain.
From social media posts and text messages to digital government documents and archives, researchers are bombarded with a deluge of text reflecting the social world. This textual data gives unprecedented insights into fundamental questions in the social sciences, humanities, and industry. Meanwhile new machine learning tools are rapidly transforming the way science and business are conducted. Text as Data shows how to combine new sources of data, machine learning tools, and social science research design to develop and evaluate new insights.
Text as Data is organized around the core tasks in research projects using text—representation, discovery, measurement, prediction, and causal inference. The authors offer a sequential, iterative, and inductive approach to research design. Each research task is presented complete with real-world applications, example methods, and a distinct style of task-focused research.
Bridging many divides—computer science and social science, the qualitative and the quantitative, and industry and academia—Text as Data is an ideal resource for anyone wanting to analyze large collections of text in an era when data is abundant and computation is cheap, but the enduring challenges of social science remain.
- Overview of how to use text as data
- Research design for a world of data deluge
- Examples from across the social sciences and industry
Vlerësime dhe komente
4,3
3 komente
Rreth autorit
Justin Grimmer is professor of political science and a senior fellow at the Hoover Institution at Stanford University. Twitter @justingrimmer Margaret E. Roberts is associate professor in political science and the Halıcıoğlu Data Science Institute at the University of California, San Diego. Twitter @mollyeroberts Brandon M. Stewart is assistant professor of sociology and Arthur H. Scribner Bicentennial Preceptor at Princeton University. Twitter @b_m_stewart
Vlerëso këtë libër elektronik
Na trego se çfarë mendon.
Informacione për leximin
Telefona inteligjentë dhe tabletë
Instalo aplikacionin "Librat e Google Play" për Android dhe iPad/iPhone. Ai sinkronizohet automatikisht me llogarinë tënde dhe të lejon të lexosh online dhe offline kudo që të ndodhesh.
Laptopë dhe kompjuterë
Mund të dëgjosh librat me audio të blerë në Google Play duke përdorur shfletuesin e uebit të kompjuterit.
Lexuesit elektronikë dhe pajisjet e tjera
Për të lexuar në pajisjet me bojë elektronike si p.sh. lexuesit e librave elektronikë Kobo, do të të duhet të shkarkosh një skedar dhe ta transferosh atë te pajisja jote. Ndiq udhëzimet e detajuara në Qendrën e ndihmës për të transferuar skedarët te lexuesit e mbështetur të librave elektronikë.
