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Found 18 papers, 6 papers with code
Recovering lost and absent information in temporal networks
The full range of activity in a temporal network is captured in its edge activity data -- time series encoding the tie strengths or on-off dynamics of each edge in the network.
The sociospatial factors of death: Analyzing effects of geospatially-distributed variables in a Bayesian mortality model for Hong Kong
However, the extent to which mortality in a geographical region is a function of socioeconomic factors in both that region and its neighbors is unclear.
Physics and Society Social and Information Networks Applications
Efficient crowdsourcing of crowd-generated microtasks
However, microtask proposal leads to a growing set of tasks that may overwhelm limited crowdsourcer resources.
Creativity in dynamic networks: How divergent thinking is impacted by one's choice of peers
Creativity is viewed as one of the most important skills in the context of future-of-work.
Social and Information Networks
UAFS: Uncertainty-Aware Feature Selection for Problems with Missing Data
Missing data are a concern in many real world data sets and imputation methods are often needed to estimate the values of missing data, but data sets with excessive missingness and high dimensionality challenge most approaches to imputation.
Inferring the size of the causal universe: features and fusion of causal attribution networks
Further, the total size of the collective causal attribution network held by humans is currently unknown, making it challenging to assess the progress of these surveys.
Neural language representations predict outcomes of scientific research
Many research fields codify their findings in standard formats, often by reporting correlations between quantities of interest.
An information-theoretic, all-scales approach to comparing networks
The Portrait Divergence reveals important characteristics of multilayer and temporal networks extracted from data.
Social and Information Networks Information Theory Information Theory Data Analysis, Statistics and Probability Physics and Society
Democratizing AI: Non-expert design of prediction tasks
Here we study how non-experts can design prediction tasks themselves, what types of tasks non-experts will design, and whether predictive models can be automatically trained on data sourced for their tasks.
Crowdsourcing Predictors of Residential Electric Energy Usage
In order to test its potential for useful application in a Smart Grid context, this paper investigates the extent to which a crowd can contribute predictive hypotheses to a model of residential electric energy consumption.
Autocompletion interfaces make crowd workers slower, but their use promotes response diversity
Creative tasks such as ideation or question proposal are powerful applications of crowdsourcing, yet the quantity of workers available for addressing practical problems is often insufficient.
What we write about when we write about causality: Features of causal statements across large-scale social discourse
Identifying and communicating relationships between causes and effects is important for understanding our world, but is affected by language structure, cognitive and emotional biases, and the properties of the communication medium.
Zipf's law is a consequence of coherent language production
The task of text segmentation may be undertaken at many levels in text analysis---paragraphs, sentences, words, or even letters.
Identifying missing dictionary entries with frequency-conserving context models
With our predictions we then engage the editorial community of the Wiktionary and propose short lists of potential missing entries for definition, developing a breakthrough, lexical extraction technique, and expanding our knowledge of the defined English lexicon of phrases.
Text mixing shapes the anatomy of rank-frequency distributions: A modern Zipfian mechanics for natural language
Natural languages are full of rules and exceptions.
Zipf's law holds for phrases, not words
With Zipf's law being originally and most famously observed for word frequency, it is surprisingly limited in its applicability to human language, holding over no more than three to four orders of magnitude before hitting a clear break in scaling.
Human language reveals a universal positivity bias
Using human evaluation of 100, 000 words spread across 24 corpora in 10 languages diverse in origin and culture, we present evidence of a deep imprint of human sociality in language, observing that (1) the words of natural human language possess a universal positivity bias; (2) the estimated emotional content of words is consistent between languages under translation; and (3) this positivity bias is strongly independent of frequency of word usage.
Link communities reveal multiscale complexity in networks
Networks have become a key approach to understanding systems of interacting objects, unifying the study of diverse phenomena including biological organisms and human society.
Physics and Society Data Analysis, Statistics and Probability Quantitative Methods
