36 research outputs found
Measuring, Predicting and Visualizing Short-Term Change in Word Representation and Usage in VKontakte Social Network
Language in social media is extremely dynamic: new words emerge, trend and
disappear, while the meaning of existing words can fluctuate over time. Such
dynamics are especially notable during a period of crisis. This work addresses
several important tasks of measuring, visualizing and predicting short term
text representation shift, i.e. the change in a word's contextual semantics,
and contrasting such shift with surface level word dynamics, or concept drift,
observed in social media streams. Unlike previous approaches on learning word
representations from text, we study the relationship between short-term concept
drift and representation shift on a large social media corpus - VKontakte posts
in Russian collected during the Russia-Ukraine crisis in 2014-2015. Our novel
contributions include quantitative and qualitative approaches to (1) measure
short-term representation shift and contrast it with surface level concept
drift; (2) build predictive models to forecast short-term shifts in meaning
from previous meaning as well as from concept drift; and (3) visualize
short-term representation shift for example keywords to demonstrate the
practical use of our approach to discover and track meaning of newly emerging
terms in social media. We show that short-term representation shift can be
accurately predicted up to several weeks in advance. Our unique approach to
modeling and visualizing word representation shifts in social media can be used
to explore and characterize specific aspects of the streaming corpus during
crisis events and potentially improve other downstream classification tasks
including real-time event detection
HyperNetX: A Python package for modeling complex network data as hypergraphs
HyperNetX (HNX) is an open source Python library for the analysis and
visualization of complex network data modeled as hypergraphs. Initially
released in 2019, HNX facilitates exploratory data analysis of complex networks
using algebraic topology, combinatorics, and generalized hypergraph and graph
theoretical methods on structured data inputs. With its 2023 release, the
library supports attaching metadata, numerical and categorical, to nodes
(vertices) and hyperedges, as well as to node-hyperedge pairings (incidences).
HNX has a customizable Matplotlib-based visualization module as well as
HypernetX-Widget, its JavaScript addon for interactive exploration and
visualization of hypergraphs within Jupyter Notebooks. Both packages are
available on GitHub and PyPI. With a growing community of users and
collaborators, HNX has become a preeminent tool for hypergraph analysis.Comment: 3 pages, 2 figure
The effect of climate change on avian offspring production: A global meta-analysis
Climate change affects timing of reproduction in many bird species, but few studies have investigated its influence on annual reproductive output. Here, we assess changes in the annual production of young by female breeders in 201 populations of 104 bird species (N = 745,962 clutches) covering all continents between 1970 and 2019. Overall, average offspring production has declined in recent decades, but considerable differences were found among species and populations. A total of 56.7% of populations showed a declining trend in offspring production (significant in 17.4%), whereas 43.3% exhibited an increase (significant in 10.4%). The results show that climatic changes affect offspring production through compounded effects on ecological and life history traits of species. Migratory and larger-bodied species experienced reduced offspring production with increasing temperatures during the chick-rearing period, whereas smaller-bodied, sedentary species tended to produce more offspring. Likewise, multi-brooded species showed increased breeding success with increasing temperatures, whereas rising temperatures were unrelated to repro- ductive success in single-brooded species. Our study suggests that rapid declines in size of bird populations reported by many studies from different parts of the world are driven only to a small degree by changes in the production of young
SVEN: An Alternative Storyline Framework for Dynamic Graph Visualization
The world is a dynamic place, so when we use graphs to help understand real world problems the structure of such graphs inevitably changes over time. Understanding this change is important, but often challenging. Techniques for general purpose dynamic graph visualizations generally fall into one of two broad categories: animation or timeline based techniques [2]. Simple approaches using animation or small multiples experience challenges with change blindness and “preserving the user’s mental map” [1]. Storyline visualization techniques [5, 7] hold promise, though these techniques were not originally designed as general purpose solutions for dynamic graph visualization