Contributors:Tur Benjamin, Antonakis John, Harstad Jennifer
Effect of Charismatic Signaling in Social Media Settings: Evidence from TED and Twitter
Given the challenges societies face on topics that are not localized (e.g., COVID-19 pandemic,
global warming), informal leadership exercised in social media currently characterizes a large
part of political and economic communication. Scholars have theorized that charismatic signaling
is effective in informal leadership settings; yet empirical evidence remains scarce in
understanding a ubiquitous phenomenon that marks our times and plays an important role in
shaping public opinion. In this paper, we used two unique data sets extracted from social media
to investigate the success of charismatic signaling in informal leadership settings. Social media
offers us a standardized medium as well as a natural environment to test our predictions. Using a
sample of TED talks and tweets, we coded for objective markers of charisma and found that
using more verbal charismatic signals predicted (a) higher views for TED talks as well as higher
ratings for the extent to which the talk was found to be inspiring (beyond attractiveness and
nonverbal behavior), and (b) more retweets. We discuss the implications of such results for both
theory and practice in the media age.
This is the OPRAmachine dataset: data collected from the OPRAmachine.com website used to track public records requests and responses from public authorities in New Jersey. This dataset is more thoroughly described in the paper "The first statewide, open access dataset tracking public records requests in New Jersey" submitted to the journal Data in Brief. Code used to produce the dataset and related figures is also included.
This repository provides additional data to accompany the paper:
"Lattice dynamics of Pnma Sn[S(1-x)Se(x)] solid solutions: energetics, phonon spectra and thermal transport"
J. M. Skelton, Journal of Physics: Energy 2, 025006 (2020), DOI: 10.1088/2515-7655/ab7839
This article examines the effect of alloying on the energetics, lattice dynamics and thermal transport of Pnma Sn[S,Se] solid solutions. This repository makes available a full set of lattice-dynamics calculations on ~1,300 structures across nine compositions, including:
* Calculated phonon density of states (DoS) curves;
* Unfolded band dispersions;
* Thermodynamic functions;
* Group velocities; and
* Two-phonon joint density of states (JDoS) functions.
In addition, the thermodynamically averaged DoS curves, unfolded dispersions, group velocities and JDoS functions discussed in the paper, calculated based on a 900 K formation temperature, are also provided.
Finally, the repository also contains input files used for the calculations, including files for the Vienna Ab initio Simulation Package (VASP) and Phonopy codes.
For details of how this data was generated, viewers are referred to the published article and supporting information. Brief details of file formats and links to further documentation are given in the included README file.
MLRSNet provides different perspectives of the world captured from satellites. That is, it is composed of high spatial resolution optical satellite images. MLRSNet contains 109,161 remote sensing images that are annotated into 46 categories, and the number of sample images in a category varies from 1,500 to 3,000. The images have a fixed size of 256×256 pixels with various pixel resolutions (~10m to 0.1m). Moreover, each image in the dataset is tagged with several of 60 predefined class labels, and the number of labels associated with each image varies from 1 to 13. The dataset can be used for multi-label based image classification, multi-label based image retrieval, and image segmentation.
The Dataset includes:
1. Images folder: 46 categories, 109,161 high-spatial resolution remote sensing images.
2. Labels folders: each category has a .csv file.
3. Categories_names. xlsx: Sheet1 lists the names of 46 categories, and the Sheet2 shows the associated multi-label to each category.
This data was obtained from an assessment using an academic procrastination scale towards 586 students in the XIII semester at Makassar, Indonesia. Students respond to statements with a Likert-scale of 5,4,3,2,1, which represents strongly agree, agree, doubt, disagree, and strongly disagree, respectively.