AAPOR 81st Annual Conference

An LA Love Story of Data, Innovation, and the Quest for Truth  

May 13 – 15, 2026 

 

AAPOR 2026, “An LA Love Story of Data, Innovation, and the Quest for Truth”, is dedicated to reaffirming the critical role of public opinion and survey research in society. In an era of shifting perceptions and evolving methodologies, the conference will focus on connecting our work to the broader public, rebuilding trust in data, and ensuring that insights from polling and survey research remain an essential pillar in informed decision-making. 

AAPOR 2026 will open with a thought-provoking keynote that will set the stage for a dynamic panel discussion with key AAPOR experts, delving into the challenges and opportunities of restoring confidence, embracing change and innovation, and communicating and maintaining relevance. 

To foster deeper conversations on key issues, AAPOR 2026 will feature five themes, each focusing on a critical area that shapes our field. As part of the conference, each theme will include a special half-day deep dive. 

The five conference themes include:

1. Survey Methods and Data Science – This track explores how data science methods (including machine learning, automation, and predictive modeling) compare to traditional survey research in both design and evaluation, particularly in the context of total survey error. Researchers are using data science to enhance survey error detection, assess data quality, and model respondent behavior, introducing new efficiencies while also raising important questions about bias, validation, and methodological rigor. AAPOR experts have played a key role in evaluating these frameworks, contributing to the broader conversation about integrating modern data science techniques into traditional survey methodologies.

2. Nonprobability and Probability Sampling – Probability sampling has long been the gold standard in survey research because it ensures every individual in a population has a known chance of being selected, leading to more representative and reliable results. However, declining response rates have made it increasingly challenging to achieve high-quality probability samples, pushing researchers to explore alternative approaches. Nonprobability methods offer faster, more cost-effective data collection but raise concerns about bias and generalizability.

3. Large Language Models and Qualitative Methods – Qualitative research has long relied on human interpretation to analyze open-ended responses, interview transcripts, and text-based data. Large language models are now being used to assist with tasks like text classification, sentiment analysis, and automated coding, offering efficiencies that help researchers process vast amounts of qualitative data. While these models introduce new capabilities, they do not replace human expertise. Instead, they can complement traditional qualitative approaches by uncovering broad patterns at scale while researchers provide the contextual nuance and ethical oversight needed for meaningful interpretation.

4. Representation and Dissemination – Leveraging Small Domain Estimation – Traditional statistical methods often rely on broad population averages, but these figures can feel disconnected from the lived experiences of individuals and communities. This track examines how researchers are working to make statistics more meaningful, ensuring that data resonates with the populations it intends to represent. As survey samples shrink and response rates decline, statistical modeling, data integration, and innovative estimation techniques are being used to produce localized, contextually relevant insights.

5. The Relevance of Polling, Official Statistics, and Public Trust – Polling, national surveys, and official statistics are more than just numbers, they are a barometer of truth, a foundation for democratic decision-making, and a public service that helps shape the future. These data sources inform policies, guide institutions, and ensure that governments remain accountable to the people they serve. But for them to fulfill their purpose, the public must not only understand them but also care about them. When data feels disconnected from real experiences, trust declines, and the ability to drive meaningful change weakens.

AAPOR 2026 is more than a gathering of experts, it is a movement to ensure that public opinion and survey research remain trusted, relevant, and impactful in shaping our collective future. 

We look forward to hosting you under the stars in L.A.! 

Morgan Earp
Conference Chair 

Emily Geisen
Associate Conference Chair 

Notice to Federal Employees:

The Annual AAPOR Conference conforms to the OPM definition of a “developmental assignment.” It is intended for educational purposes; over three quarters of time schedule is for planned, organized exchange of information between presenters and audience, thereby qualifying under section 4101 of title 5, United States Code as a training activity. The AAPOR Conference is a collaboration in the scientific community, whose objectives are to provide a training opportunity to attendees; teach the latest methodology and approaches to survey research best practices; make each attendee a better survey researcher; and, maintain and improve professional survey competency.