Sound of the crowd: wisdom of neurologists revisited

2019 ◽  
Vol 19 (6) ◽  
pp. 552-552
Author(s):  
Thanuja Dharmadasa ◽  
Matthew C. Kiernan
Keyword(s):  
Crowd Wisdom

Tracking development with Baby CROINC: The interplay of parent experience, usage, and technology approach (Preprint)

2018 ◽  
Author(s):  
Ayelet Ben-Sasson ◽  
Eli Ben-Sasson ◽  
Kayla Jacobs ◽  
Rotem Malinovitch
Keyword(s):  
Developmental Screening ◽  
Technology Competence ◽  
Proactive Approach ◽  
Crowd Wisdom ◽  
System P ◽  
Parent Experience ◽  
Wide Range ◽  
Actual Use ◽  
Perceived Usability ◽  
Crowd Intelligence

BACKGROUND To lower barriers to developmental screening, we designed Baby CROINC (CROwd INtelligence Curation), a digital platform to help parents track and assess their children’s development through crowd wisdom. OBJECTIVE To understand users’ experiences using Baby CROINC in relation to users’ technological competence and attitudes, while considering the influence of their children’s presented developmental evaluations and parents’ actual use of the system. METHODS Mothers of 260 children (M age= 17.6 months, SD=13.7) used Baby CROINC for two weeks. They entered developmental milestones on their children’s developmental diary timeline and received statistical developmental percentile reports. Mothers then completed Usability and Technology Profile Questionnaires. RESULTS Mothers’ experiences of the Baby CROINC system usability were associated with their attitudes toward solving technological problems, mediated by frequency of engagement in Internet activities. Mothers with a proactive approach toward solving technology problems, engage in a wide range of Internet activities, and/or view the Internet as integral to their lives had a better experience with Baby CROINC than mothers who did not. The system’s perceived usability was not associated with the crowd-based child developmental percentiles or quantity of mothers’ usage of the system. CONCLUSIONS Parent’s user experiences correlate with their technology competence and problem solving attitude but is not correlated with their child’s developmental status. Developmental screening platforms need to solve the tension between requiring active engagement and encouraging proactive parenting.

scholarly journals Predicting real estate market trends and value using pre-processing and sentiment text mining analysis

2021 ◽  
pp. 35-43
Author(s):  
Nikolay Sinyak ◽  
Singh Tajinder ◽  
Jaglan Madhu Kumari ◽  
Vitaliy Kozlovskiy
Keyword(s):  
Social Media ◽  
Text Mining ◽  
Real Estate ◽  
Real Estate Market ◽  
Media Analysis ◽  
Market Information ◽  
Real Estate Markets ◽  
The Real Estate ◽  
Crowd Wisdom ◽  
Market Trends

Ubiquitous growth in the text mining field is unprecedented, where social media mining is playing a significant role. Gigantic growth of text mining is becoming a potential source of crowd wisdom extraction and analysis especially in terms of text pre-processing and sentiment analysis. The analysis of a potential influence of sentiment on real estate markets controversially discussed by scholars of finance, valuation and market efficiency supporters. Therefore, it’s a significant task of current research purview which not only provide an appropriate platform for the contributors but also for active real estate market information seekers. Text mining has gained the widespread attention of real estate market information users which is almost on explosion level. Accessibility of data on such behemoth scale mandates regular and critical analysis of this information for various perspectives’ plausibility. Rich patterns of online social text can be exploited to extract the relevant real estate information effectively. As text mining plays a significant and crucial role in discovery of these insights therefore its challenges and contribution in social media analysis must be explored extensively. In this paper, we provide a brief about the current summary of the modern state of text mining in pre-processing and sentiment for the real estate market analysis. Empha-sis is placed on the resources and learning mechanism available to real estate researchers and practitioners, as well as the major text mining tasks of interest to the community. Thus, the main aim of this chapter is to expound and intellectualize the domains of social media which are accessible on an extraordinary range in the field of text mining real estate for predicting real estate market trends and value.

scholarly journals Crowd Wisdom Relies on Agents’ Ability in Small Groups with a Voting Aggregation Rule

2017 ◽  
Vol 63 (3) ◽  
pp. 818-828 ◽  
Author(s):  
Marc Keuschnigg ◽  
Christian Ganser
Keyword(s):  
Small Groups ◽  
Aggregation Rule ◽  
Crowd Wisdom

A solution to the single-question crowd wisdom problem

Nature ◽  
2017 ◽  
Vol 541 (7638) ◽  
pp. 532-535 ◽  
Author(s):  
Dražen Prelec ◽  
H. Sebastian Seung ◽  
John McCoy
Keyword(s):  
Crowd Wisdom ◽  
Single Question

scholarly journals Brain Activity Tracks Population Information Sharing by Capturing Consensus Judgments of Value

2018 ◽  
Vol 29 (7) ◽  
pp. 3102-3110 ◽  
Author(s):  
B P Doré ◽  
C Scholz ◽  
E C Baek ◽  
J O Garcia ◽  
M B O’Donnell ◽  
...  
Keyword(s):  
Daily Life ◽  
Brain Activity ◽  
Core Region ◽  
Information Value ◽  
Ventromedial Prefrontal Cortex ◽  
News Article ◽  
Social Consensus ◽  
Controlled Processing ◽  
Crowd Wisdom ◽  
Population Information

Abstract Information that is shared widely can profoundly shape society. Evidence from neuroimaging suggests that activity in the ventromedial prefrontal cortex (vmPFC), a core region of the brain’s valuation system tracks with this sharing. However, the mechanisms linking vmPFC responses in individuals to population behavior are still unclear. We used a multilevel brain-as-predictor approach to address this gap, finding that individual differences in how closely vmPFC activity corresponded with population news article sharing related to how closely its activity tracked with social consensus about article value. Moreover, how closely vmPFC activity corresponded with population behavior was linked to daily life news experience: frequent news readers tended to show high vmPFC across all articles, whereas infrequent readers showed high vmPFC only to articles that were more broadly valued and heavily shared. Using functional connectivity analyses, we found that superior tracking of consensus value was related to decreased connectivity of vmPFC with a dorsolateral PFC region associated with controlled processing. Taken together, our results demonstrate variability in the brain’s capacity to track crowd wisdom about information value, and suggest (lower levels of) stimulus experience and vmPFC–dlPFC connectivity as psychological and neural sources of this variability.

scholarly journals The disproportion of crowd wisdom: The impact of status seeking on Yelp reviews

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252157
Author(s):  
Chao Yu ◽  
Drew Margolin
Keyword(s):  
Wisdom Of Crowds ◽  
Aggregate Level ◽  
Variety Seeking ◽  
Individual Level ◽  
Price Levels ◽  
Crowd Wisdom ◽  
Status Seeking ◽  
Restaurant Reviews ◽  
The Impact ◽  
Level Analysis

This study shows that while status seeking motivates people to participate in crowdsourcing platforms, it also negatively impacts the bedrock of crowdsourcing–wisdom of crowds. Using Yelp restaurant reviews in 6 cities, we found that motivations of status seeking lead people to review a greater variety of restaurants, and achieving status further encourages this variety seeking as well as the targeting of more expensive restaurants for review. The impact of this individual-level tendency is confirmed by our aggregate-level analysis which shows that restaurants with higher price levels, higher uniqueness levels, and a larger percentage of elite reviews tend to obtain enough reviews to generate wisdom of crowds sooner than other restaurants. This leads to a different kind of distortion to crowd wisdom: an over-representation of status-conferring products and an under-representation of products that are not status-worthy. The findings suggest the importance of studying sources of distortion that are endemic to crowdsourcing itself.

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