Traditional Survey Research Research Articles

Machine learning of public sentiments towards wind energy in Norway

AbstractAcross Europe, negative public opinion has and may continue to limit the deployment of renewable energy infrastructure required for the transition to net‐zero energy systems. Understanding public sentiment and its spatio‐temporal variations is as such important for decision‐making and for developing socially accepted energy systems. In this study, we apply a sentiment classification model based on a machine learning framework for natural language processing, NorBERT, on data collected from Twitter between 2006 and 2022 to analyse the case of wind power opposition in Norway. From the 68,828 tweets with geospatial information, we show how discussions about wind power intensified in 2018/2019 together with a trend of more negative tweets up until 2020, both on a regional level and for Norway as a whole. Furthermore, we find weak geographical clustering in our data, indicating that discussions are country wide and not dominated by specific regional events or developments. Twitter data allow for detailed insight into the temporal nature of public sentiments and extending this research to additional case studies of technologies, countries and sources of data (e.g. newspapers, other social media) may prove important to complement traditional survey research and the understanding of public sentiment.

Lessons Learned and Possibilities Recognized: An Academic-Community Partnership to Engage Multicultural Populations During a Pandemic

The COVID-19 pandemic exposed multiple disparities; racial and ethnic minority groups experienced higher proportions of cases, hospitalizations, and deaths. However, racial and ethnic minority populations are often underrepresented in traditional survey research. In a survey of the social and economic impacts of COVID-19 in a local area, we developed three distinct academic-community partnerships. We report these partnerships with particular focus on the partnership that promoted the inclusion of racially and ethnically minoritized multicultural populations in the survey. We describe each stage of the partnership, including survey design, translation, outreach and recruitment, results, and dissemination of results, and share the lessons learned, both in terms of academic-community partnerships and in surveying multicultural populations. Our lessons learned consist of four main themes: Outreach and recruitment is more labor-intensive with multicultural populations; the respondents in the targeted sample for this study differed from the general population in how they experienced the effects of COVID-19; researchers must be flexible and plan for more time and expenses; and academic-community partnerships are a valuable model for including traditionally hard-to-reach populations in research. A comparison of our survey reach to that of its corresponding representative survey affirms that our process was effective in recruiting a population that differed from the representative sample, both in terms of demographics and the severity of the pandemic’s impact at the household level. Thus, additional efforts to reach multicultural and underrepresented populations are warranted, especially during a pandemic, and academic-community partnerships combine multiple areas of expertise to productively engage such populations.

The Information Seeking Behaviors and Needs of Suicide Survivors During Bereavement

Abstract The suicide of one person impacts 60 people, known as suicide survivors. These survivors are at an increased risk for negative mental health outcomes including PTSD, suicidal ideation, and suicide contagion. Despite these consequences, there have not been any information science studies that have explored the information behaviors of people who have recently survived the suicide of a loved one. This article takes a unique approach in combining autoethnography with traditional survey research. One hundred and ninteen participants sourced from a private Facebook suicide bereavement group responded to a survey asking them about their information-seeking after a loved one committed suicide. The qualitative data were fragmented and grouped into like-responses and thematic codes that gave explanation to the research questions. These results are coupled with the author’s ethnographic recounting of a similar experience. Brenda Dervin’s sense-making is employed as the methodological lens through which the study is conducted. It is found that suicide survivors are highly unlikely to have their informational needs met. In the immediate aftermath of their loss, they are most likely to look for information related to the suffering of the deceased. As time passes, they begin to look for information about coping with their loss and preventing suicide of other people; either those close to them or in a larger community scale. Being a survivor motivated many participants to advocacy work. Finally, the author argues that the findings of this article should compel further research and the creation of information policy to aid survivors and prevent suicide contagion.

Elucidating College Students’ Stressors: Photovoice as a Pedagogical Tool and Qualitative Methodology

Traditional research examining student stress relies on surveys using pre-determined categories. This study diverts from that approach by adopting a Communication in Conflict class assignment over seven classes (N = 115) using photovoice to determine if results fluctuate by using a different methodology. Additionally, we sought to understand if the sources of stress vary by gender and semester. The data revealed seven categories as the main stressors of student conflict: 1) time management, 2) mental health, 3) finding oneself, 4) future uncertainty, 5) other, 6) financial, and 7) past mistakes. Regardless of participants’ sex/gender or semester in which the data were collected, time management and mental health remained constant. Furthermore, finding oneself and future uncertainty were stressors identified more often in the fall rather than the spring semester. These results varied from traditional survey research.

How low can we go? Declining survey response rates to new zealand electoral roll mail surveys over three decades

ABSTRACT Quality survey research relies on the willingness of the public to participate, but survey response rates are decreasing over time. This research note explores response rate data from several national probability sample mail surveys drawn from a consistent sampling frame (the New Zealand electoral roll) over the past 30 years. The aim of this work is to document the scale of the response rate decline problem in mail survey studies, predict future response rates, and track nonresponse bias through comparing self-reported voter turnout in surveys to official turnout. We use data from the New Zealand Election Study, the International Social Survey Programme, the New Zealand edition of the World Values Survey, and the New Zealand Attitudes and Values Study. Our findings demonstrate that there has been a consistent downward trend in response rates and an increase in nonresponse bias for self-reported voter turnout. Response rates in the early 1990s were as high as 72%, before dropping to the 60% range around the year 2000, with response rates effectively halving from their early 1990s rates by 2015. We comment on the implications for future surveys, voter enrolment, local government turnout, and political polling. Ultimately, these results leave us with the question of how long traditional mail survey research will be able to continue.

What’s the Benefit of a Video? The Effect of Nonmaterial Incentives on Response Rate and Bias in Web Surveys

Traditional survey research faces declining response rates due to changing cultural habits and technological developments. Researchers have developed novel approaches to increase respondents’ likelihood of participating in web surveys. However, we lack information about whether these methods indeed increase response rates and, if so, whether they bias the resulting data. This article focuses on the use of nonmaterial incentives in the form of a video that provides the invitees with information tailored to their life situation. Analysis of our experimental data shows that instead of increasing respondents’ probability of starting the survey, the video treatments actually decrease it. We provide evidence that the lower salience of the intrinsic benefits of survey participation in the invitation email significantly contributes to this reduction. Additionally, the effect of the nonmaterial incentive differs across subgroups, affecting nonresponse biases in line with employment status, gender, and migration background. We therefore conclude that using additional information in the form of a video as a nonmaterial survey incentive is only suitable under specific conditions.

Electoral and Public Opinion Forecasts with Social Media Data: A Meta-Analysis

In recent years, many studies have used social media data to make estimates of electoral outcomes and public opinion. This paper reports the findings from a meta-analysis examining the predictive power of social media data by focusing on various sources of data and different methods of prediction; i.e., (1) sentiment analysis, and (2) analysis of structural features. Our results, based on the data from 74 published studies, show significant variance in the accuracy of predictions, which were on average behind the established benchmarks in traditional survey research. In terms of the approaches used, the study shows that machine learning-based estimates are generally superior to those derived from pre-existing lexica, and that a combination of structural features and sentiment analyses provides the most accurate predictions. Furthermore, our study shows some differences in the predictive power of social media data across different levels of political democracy and different electoral systems. We also note that since the accuracy of election and public opinion forecasts varies depending on which statistical estimates are used, the scientific community should aim to adopt a more standardized approach to analyzing and reporting social media data-derived predictions in the future.

Smart(phone) Approaches to Mobile App Data Collection

The conduct of high-quality survey research is challenged by declining participation rates, associated rising costs to meet recruitment goals, poor coverage, and inadequate sampling frames, leading to greater nonresponse errors. In addition, when surveys remain active for extended periods of time to increase response rates, the time between data collection and analysis is long, which makes it difficult to address time-sensitive urgent problems or crises. Solutions to tackle these important data collection concerns must expand beyond traditional survey research methodologies and include a multidisciplinary approach. We conducted a pilot study funded by the Council of State and Territorial Epidemiologists through a cooperative agreement with the Substance Abuse and Mental Health Services Administration\* to evaluate the feasibility of conducting surveys via a mobile app. The focus was to determine whether conducting surveys via a mobile app could be rapid, valid, and low burden while simultaneously testing a gamified design feature and limitations of this approach. We evaluated the feasibility of using a mobile app survey data collection method to reach college students regardless of their location, reduce the burden of survey response, and collect valid data more quickly than traditional survey methods allow. We had six primary objectives: (1) determine if students would download the survey app, (2) assess the representativeness of the study participants using the app, (3) determine how well the app can retain individuals across three survey waves, (4) explore whether simple gamification within the app would improve response rates across survey waves, (5) assess the rapidity of survey completions, and (6) understand the overall app user experience. \*Funding for this project was administered by the Council of State and Territorial Epidemiologists through a cooperative agreement with the Substance Abuse and Mental Health Services Administration agreement 14-OA-22-20-206.

Integrating Geographic Information into Survey Research: Current Applications, Challenges and Future Avenues

Geographic information science (GIScience) offers survey researchers a plethora of rapidly evolving research strategies and tools for data acquisition and analysis. However, the potential for incorporating geographic information systems (GIS) tools into traditional survey research has not yet been fully appreciated by survey researchers. In this article, we provide a comprehensive overview of recent advances and challenges in leveraging this potential. First, we present state-of-the-art applications of GIS tools in traditional survey research, drawing mainly on examples from psychological survey research (e.g., socioecological psychology). We also discuss innovative GIS tools (e.g., wearables) and GIScience methods (e.g., citizen sensing) that expand the scope of traditional surveys. Second, we highlight a number of challenges and problems (e.g., choice of spatial scale, statistical issues, privacy concerns) and - where possible - suggest remedies. With increasing awareness of the potential that GIS tools hold for survey research, and intensified dialogue between researchers from both sides, more fruitful collaboration appears within reach.

Microsoft Office: Gaining Insight into the Life of a College Student (A)

Microsoft Office was facing an uphill task in engaging the undergraduate student community. Attracting this audience—the most tech-savvy generation ever—was critical to the future of the Microsoft Office franchise. Microsoft's past advertising efforts to reach this audience had proven lackluster, while its key competitors were gradually entrenching themselves among this demographic. Microsoft's challenge was to determine the best tactics that could successfully connect with this audience. The (A) case describes Microsoft's dilemma and briefly addresses what college students mostly care about: managing homework, creating great-looking schoolwork, preparing for the workplace, and collaborating with friends and classmates. It also provides competitive information, chiefly Google's increasing presence in universities and its focus on the higher education market and the growing influence of Facebook among students and its evolution into a productivity tool. The (B) case describes the qualitative research tools that Microsoft used to get a better understanding of college students: day diaries using Twitter, technology diaries using the Internet and smartphones, focus groups, and one-on-one interviews with students. The case helps students understand the value of ethnographic and qualitative research techniques, draw inferences from the data, and subsequently make recommendations. It illustrates how ethnographic and observational studies enrich research by generating deeper consumer insight than traditional methods.Students will learn: - How online tools in ethnographic and observational research offer new insights not revealed by traditional survey research - How different qualitative market tools are used to collect data, as well as the pros and cons of different ethnographic research techniques - To interpret and synthesize data from qualitative and ethnographic research - How research can influence a firm's marketing and advertising tactics

Microsoft Office: Gaining Insight into the Life of a College Student (B)

Microsoft Office was facing an uphill task in engaging the undergraduate student community. Attracting this audience—the most tech-savvy generation ever—was critical to the future of the Microsoft Office franchise. Microsoft's past advertising efforts to reach this audience had proven lackluster, while its key competitors were gradually entrenching themselves among this demographic. Microsoft's challenge was to determine the best tactics that could successfully connect with this audience. The (A) case describes Microsoft's dilemma and briefly addresses what college students mostly care about: managing homework, creating great-looking schoolwork, preparing for the workplace, and collaborating with friends and classmates. It also provides competitive information, chiefly Google's increasing presence in universities and its focus on the higher education market and the growing influence of Facebook among students and its evolution into a productivity tool. The (B) case describes the qualitative research tools that Microsoft used to get a better understanding of college students: day diaries using Twitter, technology diaries using the Internet and smartphones, focus groups, and one-on-one interviews with students. The case helps students understand the value of ethnographic and qualitative research techniques, draw inferences from the data, and subsequently make recommendations. It illustrates how ethnographic and observational studies enrich research by generating deeper consumer insight than traditional methods.Students will learn: - How online tools in ethnographic and observational research offer new insights not revealed by traditional survey research - How different qualitative market tools are used to collect data, as well as the pros and cons of different ethnographic research techniques - To interpret and synthesize data from qualitative and ethnographic research - How research can influence a firm's marketing and advertising tactics

Variation in Sexual Identification Among Behaviorally Bisexual Women in the Midwestern United States: Challenging the Established Methods for Collecting Data on Sexual Identity and Orientation

Collecting information on sexual identity is critical to ensuring the visibility of minority populations who face stigmatization and discrimination related to sexual identities. However, it is challenging to capture the nuances of sexual identity with traditional survey research methods. Using a mixed-methods approach, we gathered data on the sexual identities of 80 behaviorally bisexual women in the Midwestern United States through an online survey. When provided different types of measures (e.g., open ended and fixed response) and different contexts in which to identify (e.g., private and public), participants varied in how they reported their sexual identities. Qualitative analysis of participant narratives around identity change finds partitioning and ranking of attraction is a key component in understanding behaviorally bisexual women's identities. We further identify a division regarding the desired outcomes of identity development processes. Given the multiple ways in which participants identified depending upon the type of measure and the context specified, and the variation in identification over time, results support reconsidering the capability of typical measures and methods used in survey research to capture sexual identity information. Additionally, findings highlight the utility of including multiple, context-specific measures of sexual identities in future research.

Wiki surveys: open and quantifiable social data collection.

In the social sciences, there is a longstanding tension between data collection methods that facilitate quantification and those that are open to unanticipated information. Advances in technology now enable new, hybrid methods that combine some of the benefits of both approaches. Drawing inspiration from online information aggregation systems like Wikipedia and from traditional survey research, we propose a new class of research instruments called wiki surveys. Just as Wikipedia evolves over time based on contributions from participants, we envision an evolving survey driven by contributions from respondents. We develop three general principles that underlie wiki surveys: they should be greedy, collaborative, and adaptive. Building on these principles, we develop methods for data collection and data analysis for one type of wiki survey, a pairwise wiki survey. Using two proof-of-concept case studies involving our free and open-source website www.allourideas.org, we show that pairwise wiki surveys can yield insights that would be difficult to obtain with other methods.

Beyond Probability Sampling: Population Inference in a World without Benchmarks

In recent years, proponents of non-probability sample surveys and alternative data collection techniques have questioned the foundations of traditional survey research. Although evidence of large biases using traditional methods has not yet emerged, declining response rates and rising costs may soon usher in a new paradigm in the survey world. This paper proposes a conceptual foundation for considering the reliability and likely accuracy of estimates as we shift from a reliance on traditional survey design to a set of conclusions that depend inherently on statistical models and the assumptions they engender. Specifically, it argues that research results can be trusted when reliable results emerge across data sources affected by very different types of survey errors. Conditions necessary for reliable conclusions are proposed.

A new approach to psychological measures in leadership research

Is survey data a source of new information, or could surveys just be begging their questions? The authors of this opinion piece suspect that survey data in leadership research do not reflect attitudes to workplace phenomena. Instead, they may just be assessments of the similarity of the language in the applied items. In a recent article in the journal PLOS ONE, this possibility was tested in a new theory called the semantic theory of survey responses (STSR). In a follow-up study, language links leadership to other phenomena such as heroism, in ways that are difficult to entangle by traditional survey research.

Beyond Survey Self-Reports: Using Physiology to Tap Political Orientations

Abstract Some aspects of our attitudes are composed of things outside of our consciousness.However, traditional survey research does not use measurements that are able to tapinto these aspects of public opinion. We describe, recommend, and demonstrate aprocedure by which non-self-reported responses can be measured in order to testwhether these responses have independent effects on individuals’ preferences. Weuse one of the better-known physiological measures—electrodermal activity or skinconductance—and illustrate its potential by reporting our own study of attitudestoward President Barack Obama. We find that both self-reported emotional responsesand physiological responses to Obama’s image independently correlate with variationin the intensity of attitudes regarding his job approval and his central policy proposal:health-care reform. How is an individual’s response to a political concept, event, person, or objectbest measured? For most social scientists, the answer is simple: ask theindividual to self-report responses or mental/emotional states. Self-reports,

Social Media in Public Opinion Research: Executive Summary of the Aapor Task Force on Emerging Technologies in Public Opinion Research

Public opinion research is entering a new era, one in which traditional survey research may play a less dominant role. The proliferation of new technologies, such as mobile devices and social-media platforms, is changing the societal landscape across which public opinion researchers operate. As these technologies expand, so does access to users� thoughts, feelings, and actions expressed instantaneously, organically, and often publicly across the platforms they use. The ways in which people both access and share information about opinions, attitudes, and behaviors have gone through a greater transformation in the past decade than perhaps in any previous point in history, and this trend appears likely to continue. The ubiquity of social media and the opinions users express on social media provide researchers with new data-collection tools and alternative sources of qualitative and quantitative information to augment or, in some cases, provide alternatives to more traditional data-collection methods. The reasons to consider social media in public opinion and survey research are no different than those of any alternative method. We are ultimately concerned with answering research questions, and this often requires the collection of data in one form or another. This may involve the analysis of data to obtain qualitative insights or quantitative estimates. The quality of data and the ability to help accurately answer research questions are of paramount concern. Other practical considerations include the cost efficiency of the method and the speed at which the data can be collected, analyzed, and disseminated. If the combination of data quality, cost efficiency, and timeliness required by a study can best be achieved through the use of social media, then there is reason to consider these methods for research. An additional reason to consider social media in public opinion and survey research is its explosion in popularity over the past several years. �

Capturing the Multiple and Shifting Identities of Farm Women in the Northeastern United States

AbstractThe identities of women on farms are shifting as more women enter farming and identify as farmers, as reflected by the 30 percent growth in women farmers in the U.S. census of agriculture (USDA 2009). This article draws from identity theory to develop a quantitative measure of the identities of farm women. The measure incorporates multiple roles farming women may perform and weights these roles by their salience to two farm identities, farm operator and farm partner. We use a sample of women on farms (n = 810) in the northeastern United States to assess the measures of role identity in relation to reported decision‐making authority, farm tasks, and farm and individual characteristics. The findings provide a multidimensional view of farming women in the northeastern United States, a far more complex view than traditional survey research has previously captured. This research provides a measure that other researchers can use to assess the multiple and shifting identities of farming women in other sections of the United States.

Can Marketing Data Aid Survey Research? Examining Accuracy and Completeness in Consumer-File Data

Survey research depends crucially on its ability to collect data from a targeted sample and for that sample to mirror the population of interest. Increasingly, survey firms are using data purchased from marketing firms such as Experian and Acxiom (consumer-file marketing data) as a means to improve correspondence between survey respondents and the general public. These data hold tremendous promise, not only for sampling at a reduced cost, but also for allowing researchers to adjust biases that often occur across groups in traditional survey research. Though these new techniques are gaining momentum and currency, there is to date no published research comparing marketing data to more traditionally sampled data. The benefits from using marketing data depend in part on whether the data are both accurate and complete. This paper is the first to systematically assess the quality of one source of consumer-file marketing data. Using a unique data set compiled by GfK KnowledgePanel®, we compare this source of ancillary marketing data with self-report data on the same respondents to determine the correspondence between the two. We also evaluate conditions under which consumer-file data are missing to determine whether patterns in missing data might introduce systematic biases when data are analyzed. Results indicate that the ancillary data differ from self-reported data on a variety of demographic factors. Further, data were missing in patterns that could not be easily addressed. The findings urge caution for those who hope to improve survey administration and design using currently available consumer-file data.

Creating strategic commitment in franchise systems: establishing the link between leadership, organizational structure, and performance

In this paper, we address the issue of strategic commitment in franchise systems by exploring the impact of several structural and leadership characteristics. Specifically, we examine the role of leadership style, organizational openness, and organizational structure in the strategic commitment–performance relationship. Our analysis is accomplished through the use of traditional survey research methods with seven franchise systems in multiple industries in the United States. We demonstrate that more committed franchisees execute the corporate strategy and have more open communication, which leads to greater performance. Finally, we formulate a set of normative recommendations for how franchisors and franchisees can better organize, communicate, and execute.