Networks of Gratitude: Structures of Thanks and User Expectations in Workplace Appreciation Systems

Appreciation systems--platforms for users to exchange thanks and praise--are becoming common in the workplace, where employees share appreciation, managers are notified, and aggregate scores are sometimes made visible. Who do people thank on these systems, and what do they expect from each other and their managers? After introducing the design affordances of 13 appreciation systems, we discuss a system we call Gratia, in use at a large multinational company for over four years. Using logs of 422,000 appreciation messages and user surveys, we explore the social dynamics of use and ask if use of the system addresses the recognition problem. We find that while thanks is mostly exchanged among employees at the same level and different parts of the company, addressing the recognition problem, managers do not always act on that recognition in ways that employees expect.Comment: in Tenth International AAAI Conference on Web and Social Media, 201

Caveat Emptor, Computational Social Science: Large-Scale Missing Data in a Widely-Published Reddit Corpus

As researchers use computational methods to study complex social behaviors at scale, the validity of this computational social science depends on the integrity of the data. On July 2, 2015, Jason Baumgartner published a dataset advertised to include ``every publicly available Reddit comment'' which was quickly shared on Bittorrent and the Internet Archive. This data quickly became the basis of many academic papers on topics including machine learning, social behavior, politics, breaking news, and hate speech. We have discovered substantial gaps and limitations in this dataset which may contribute to bias in the findings of that research. In this paper, we document the dataset, substantial missing observations in the dataset, and the risks to research validity from those gaps. In summary, we identify strong risks to research that considers user histories or network analysis, moderate risks to research that compares counts of participation, and lesser risk to machine learning research that avoids making representative claims about behavior and participation on Reddit

Networked tactics for gender representation in the news

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2013.Page 108 blank. Cataloged from PDF version of thesis.Includes bibliographical references (p. 102-107).This thesis presents research on gender disparities in online news, followed with three open source designs that attempt to address those disparities. Open Gender Tracker is a platform that applies automated gender analysis to electronic content sources. FollowBias is a behavioral experiment on the effectiveness of personal trackers to manage the biases of journalists and curators. Passing On uses data and stories to attract and coordinate participants to expand the visibility of women in Wikipedia. These three designs are offered as inspirations for a paradigm of technologies to measure and change women's representation in the news.by J. Nathan Matias.S.M

Do Automated Legal Threats Reduce Freedom of Expression Online? Results from a Natural Experiment

Automated law enforcement systems support privately-operated enforcement bots to take legal action in hundreds of millions of cases a year. In the area of copyright, legal scholars have hypothesized the existence of “chilling effects” that harm public discourse by influencing people to self-censor protected speech. We test this hypothesis in a large-scale quasi-experiment with 9,818 accounts on Twitter that made 5,171,111 tweets. In a confirmatory interrupted time-series analysis, we find evidence that people reduce how much they post online after receiving a take-down notice from a copyright enforcement bot. On average, accounts sent fewer tweets after enforcement (p\u3c0.001). Accounts also changed from a daily increase in public tweets to a decline on average (p\u3c0.001). We also report on novel software that conducts third-party monitoring of the behavioral outcomes of automated law-enforcement systems. Since automated law enforcement can influence public discourse, third-party monitoring like this report will be essential to governing the power of enforcement algorithms in society

MagAO Imaging of Long-period Objects (MILO). I. A Benchmark M Dwarf Companion Exciting a Massive Planet around the Sun-like Star HD 7449

We present high-contrast Magellan adaptive optics (MagAO) images of HD 7449, a Sun-like star with one planet and a long-term radial velocity (RV) trend. We unambiguously detect the source of the long-term trend from 0.6-2.15 \microns ~at a separation of \about 0\fasec 54. We use the object's colors and spectral energy distribution to show that it is most likely an M4-M5 dwarf (mass \about 0.1-0.2 \msun) at the same distance as the primary and is therefore likely bound. We also present new RVs measured with the Magellan/MIKE and PFS spectrometers and compile these with archival data from CORALIE and HARPS. We use a new Markov chain Monte Carlo procedure to constrain both the mass ($> 0.17$ \msun ~at 99$\%$ confidence) and semimajor axis (\about 18 AU) of the M dwarf companion (HD 7449B). We also refine the parameters of the known massive planet (HD 7449Ab), finding that its minimum mass is $1.09^{+0.52}_{-0.19}$ \mj, its semimajor axis is $2.33^{+0.01}_{-0.02}$ AU, and its eccentricity is $0.8^{+0.08}_{-0.06}$. We use N-body simulations to constrain the eccentricity of HD 7449B to $\lesssim$ 0.5. The M dwarf may be inducing Kozai oscillations on the planet, explaining its high eccentricity. If this is the case and its orbit was initially circular, the mass of the planet would need to be $\lesssim$ 1.5 \mj. This demonstrates that strong constraints on known planets can be made using direct observations of otherwise undetectable long-period companions.Comment: Corrected planet mass error (7.8 Mj --> 1.09 Mj, in agreement with previous studies

Resource pulse in shallow waters: characterization of the scavenger community associated with a dolphin carcass

OCEANS 2023, 05-08 June 2023, Limerick.-- 5 pages, 3 figures, 3 tables.-- © 20XX IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksNumerous studies have focused on the scavenger communities that feed on the carcasses of large marine animals, such as whales, in deep-sea habitats. Yet, there are far fewer studies in shallow water ecosystems and especially in the Mediterranean. Here, we performed an artificial cetacean fall in shallow waters in the northwestern Mediterranean. The cetacean carcass was monitored by via 30-min time-lapse photos using a fixed camera. We observed that bony fish were the main scavenger taxa. In addition, different species arrived at different times perhaps reflecting their role as scavengers or active predatorsWe thank the financial support from the Spanish government through the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S)Peer reviewe