Online Crowdsourcing Platform Research Articles

Looking South

Mobile and social technologies are providing new opportunities to document, characterize, and gather impressions of urban environments. In this article, we present a study that examines urban perceptions of three cities in central Mexico; the study integrates a mobile crowdsourcing framework to collect geo-localized images of urban environments by a local youth community, an online crowdsourcing platform to gather impressions of urban environments along 12 physical and psychological dimensions, and a deep learning framework to automatically infer human impressions of outdoor urban scenes. Our study resulted in a collection of 7,000 geo-localized images containing outdoor scenes and views of each city’s built environment, including touristic, historical, and residential neighborhoods, and 144,000 individual judgments from Amazon Mechanical Turk. Statistical analyses show that outdoor environments can be assessed in terms of interrater agreement for most of the urban dimensions by the observers of crowdsourced images. Furthermore, we proposed a methodology to automatically infer human perceptions of outdoor scenes using a variety of low-level image features and generic deep learning (CNN) features. We found that CNN features consistently outperformed all the individual low-level image features for all the studied urban dimensions. We obtained a maximum R 2 of 0.49 using CNN features; for 9 out of 12 labels, the obtained R 2 values exceeded 0.44.

Association of exercise with smoking-related symptomatology, smoking behavior and impulsivity in men and women

IntroductionDespite extensive efforts to develop effective smoking cessation interventions, 70–85% of American cigarette smokers who quit relapse within one year. Exercise has shown promise as an intervention; however, many results have been equivocal. This study explored how exercise is associated with smoking-related symptomatology, smoking behavior and impulsivity in male and female smokers. MethodsParticipants were recruited throughout the United States using the on-line crowdsourcing platform, Amazon’s Mechanical Turk. They completed a survey with self-report measures assessing exercise, smoking-related symptomatology, smoking behavior and impulsivity. Differences between men and women were tested using t- and chi-square tests. Regression analyses tested for associations between exercise and smoking-related symptomatology, smoking behavior and impulsivity. ResultsParticipants (N = 604) were, on average, 32 (SD = 6.2) years old, mostly Caucasian, with at least some college education and approximately half were women. Women exercised slightly less than men and had more negative affect, craving, physical symptoms and withdrawal. Women smoked more cigarettes per day, had greater nicotine dependency and more years of smoking. Positive affect was positively associated with exercise for both men and women; however, this association was significantly stronger in women. Negative affect and withdrawal were inversely associated with exercise for women only. Impulsivity was inversely associated with exercise for both men and women. ConclusionExercise was significantly associated with several smoking-related symptomatology, smoking behavior and impulsivity variables for both men and women, suggesting that exercise may be a useful intervention for smoking cessation. Future prospective research should determine how exercise directly impacts smoking cessation.

The sleep and sex survey: Relationships between sexual function and sleep

ObjectiveDistress and dysfunction in sleep and sex are both very common, and have been found to be separately related to anxiety, depression, and stress. Even so, and despite evidence linking obstructive sleep apnea and erectile disfunction, the connections between sleep and sex are largely understudied. MethodA large (N = 703) survey of people in the United States between 18 and 65 years old was conducted using Mechanical Turk, an on-line crowd-sourcing platform. Approximately 30% of participants were Black, Hispanic, Asian, or Native American, 8% identified as lesbian, gay or bisexual, and the sampling structure ensured an even gender distribution in each of 5 age strata. The Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), International Index of Erectile Function (IIEF), and Female Sexual Function Index (FSFI) assessed sleep and sexual dysfunction; the Perceived Stress Scale (PSS), Patient Health Questionnaire (PHQ-9), and General Anxiety Disorder scale (GAD-7) measured stress, depression, and anxiety to measure variance. ResultsWe found a significant connection between insomnia severity and sexual function. The relationship remained significant after accounting for the shared variability associated with depressive and anxious symptoms, and perceived stress. ConclusionGiven this relationship, clinicians observing dysfunction in one area should routinely assess for dysfunction in the other. Further research will be required to determine (a) if treatment of one has an effect on the other, and (b) if this connection is related to a common psychopathological factor and/or is a conditioned association related to the commonly shared context of bed.

A Copycat Penalty: Micro Evidence From an Online Crowdsourcing Platform

Open innovation platforms that enable organizations to crowdsource ideation to parties external to the firm are proliferating. In many cases, the platforms use open contests that allow the free exchange of ideas with the goal of improving the ideation process. In open contests, participants (“solvers”) observe the ideas of others as well as the feedback received from the contest sponsor (“seeker”). The open nature of such contests generate incentives for imitating successful early designs by future solvers at the cost of the original solvers. As such, this creates the possibility of the platform unraveling when original solvers strategically withdraw from the platform, expecting their ideas will be copied without recompense. To investigate agent behavior in such a setting, we analyze publicly accessible micro-data on more than 6,000 design contests, submissions and participants from crowdsourced open ideation platforms and augment this analysis with field and online experiments. These data include the original image files submitted to the contests, which enable us to compare how similar one image is to another using a customized ensemble image comparison algorithm. We find that better rated designs are likely to be imitated by later entering solvers, thereby generating significant risk to early entrants that their ideas will be appropriated by later entrants without recompense. As a countervailing force, we document that seekers tend to reward original designs, and avoid picking as winners those that seem to be imitating and free-riding. Seekers perceive original designers as more competent, informing their design choice. These patterns suggest that market behavior on such platforms may have a self-policing component that disincentivizes excessive imitation, rewards originality and prevents unraveling.

Humor norms for 4,997 English words

Humor ratings are provided for 4,997 English words collected from 821 participants using an online crowd-sourcing platform. Each participant rated 211 words on a scale from 1 (humorless) to 5 (humorous). To provide for comparisons across norms, words were chosen from a set common to a number of previously collected norms (e.g., arousal, valence, dominance, concreteness, age of acquisition, and reaction time). The complete dataset provides researchers with a list of humor ratings and includes information on gender, age, and educational differences. Results of analyses show that the ratings have reliability on a par with previous ratings and are not well predicted by existing norms.

Doing Good Online: An Investigation into the Characteristics and Motivations of Digital Volunteers

The rapid growth in Internet technology is making it possible to volunteer in online settings, with participants able to contribute directly to research-based activities supporting non-profit groups and charitable organisations. This study undertakes an investigation into the profile and motivations of contributors to these online volunteering projects. We specifically investigate volunteer activity and retention for the online crowdsourcing platform known as the Zooniverse, which is home to around thirty online volunteering projects. Through a survey undertaken with a representative sample of contributors and reconciling against records of actual voluntary activity, we are able to measure motivations against the Volunteer Functions Inventory (VFI) and explore relationships with observed levels of activity and retention. Our results show that a unique combination of ‘other’ and ‘self’ oriented motivation, specifically Protective & Enhancement, Values and particularly Understanding, associate significantly and positively with observed variations in volunteering activity and retention in an online setting.

Crowdsourcing data collection of the retail tobacco environment: case study comparing data from crowdsourced workers to trained data collectors

ObjectiveTo assess whether crowdsourcing is a viable option for conducting surveillance of point of sale (POS) tobacco marketing practices.MethodsWe posted jobs to an online crowdsourcing platform to audit 194 Florida...