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AAPOR
The leading association
of public opinion and
survey research professionals
American Association for Public Opinion Research

Mobile Data Collection and New Technology

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Member Price: $130.00
Nonmember Price: $175.00

Student pricing available


Data Science Trends and Tools for Measuring Attitudes and Behaviors
About This Course:

In its broadest sense, “data science” is an interdisciplinary field about scientific methods, processes, and systems to extract information and insights from data in various forms – designed or organic, structured or unstructured. Working across a wide range of topic domains, data science approaches are now used routinely in the commercial sector for measuring or drawing conclusions about people’s attitudes and behaviors and becoming more commonplace in other sectors as well. Operating parallel to or in conjunction with more traditional statistical survey research approaches, data science is having a transformative effect on the ways in which researchers seek to understand attitudes and behaviors. In this webinar we explore some of the major trends in data science as it pertains to the measurement of attitudes and behaviors as well as its relationship with traditional survey approaches. We then discuss at a conceptual level some of the key tools and approaches being used and how they are being applied in the field. In doing so we take a closer look at three of the more widely used areas: machine learning, text analytics, and data visualization. We conclude with a look at where the field of data science is going and its longer term implications for how we measure and understand attitudes and behaviors.

Learning Objectives: 

  • Understanding the field of data science and how it relates to traditional statistical survey research efforts.
  • Identifying some of the key methods and tools being used in the field and how they might be applied.
  • Delineating some of the key advantages and disadvantages of data science approaches for understanding attitudes and behaviors.


A Primer to Web Scraping with R
About This Course:

This course provides an overview of the use of short message service (SMS) text messaging in survey research. We review the environmental contexts (e.g, samples and online panels) in which SMS is used in survey research and the still-developing ramifications of the TCPA. We will discuss the promise and perils of using SMS as a tool for recruitment and reminders, before turning to its use as a mode for data collection, including asking conventional survey questions and measuring behavior and attitudes in a diary-like format. The course will wrap-up with a discussion of the major tools currently available on the market for integrating SMS into a production survey.

Learning Objectives:
  • Gain an understanding of the uses of historical and current uses of text messaging for Survey Research.
  • Gain specific understanding about how SMS can be used to contact, recruit, remind, and measure.
  • Get ideas for how to include SMS in your survey protocols.


Improving Surveys with Paradata: Making Use of Process Information
About this Course

This is an introductory course designed to cover the paradata topic in three parts. The first part will cover the role of paradata within the Total Survey Error Framework. For each step in the survey production process, the potential of paradata to estimate or reduce the respective error will be discussed. The second part will showcase individual surveys in which paradata have been used. Research examples will be discussed, including but not limited to the use of paradata to monitor fieldwork activity, guide intervention decisions and perform post-hoc analyses. The course will close with a discussion of challenges and current research problems in the use of paradata.

Learning Objectives
  • Identify paradata along the production process.
  • Summarize challenges when collecting and using paradata.
  • Develop ideas for the use of paradata in the participants' own surveys.