Screen shot 2020 05 04 at 4.02.46 pm

Josh Nicholson

and 1 more

Hello, and welcome to Authorea!👋  We're happy to have you join us on this journey towards making writing and publishing smoother, data-driven, interactive, open, and simply awesome. This document is a short guide on how to get started with Authorea, specifically how to take advantage of some of our powerful tools. Of course, feedback and questions are not only welcome, but encouraged--just hit the comment icon at the top of the document 💬and join the conversation.The BasicsAuthorea is a document editing and publishing system built primarily for researchers. It allows you to collaborate on documents and publish them easily. Each Authorea document can include data, interactive figures, and code. But first, let's get started! 1. Sign up.If you're not already signed up, do so at  Tip: if you are part of an organization, sign up with your organizational email.  2. First stepsDuring the signup process you will be asked a few questions: your location, your title, etc. You will be also prompted to join a group. Groups are awesome! They allow you to become part of a shared document workspace. Tip: during signup, join a group or create a new one for your team. Overall, we suggest you fill out your profile information to get the best possible Authorea experience and to see if any of your friends are already on the platform. If you don't do it initially during sign up, don't worry; you can always edit your user information in your settings later on.Once you've landed on your profile page (see below). There are a few things you should immediately do:Add a profile picture. You've got a great face, show it to the world :) For reference, please see Pete, our chief dog officer (CDO), below. Add personal and group information. If you haven't added any personal information, like a bio, a group affiliation, your ORCID, or your location, do it! You might find some people at your organization already part of Authorea, plus it is a great way to build your online footprint, which is always good for getting jobs.
Poster ischool small
How do we collectively feel about our future? Do we look forward to it with anxiety or vigor? Are we apprehensive or optimistic of what the future will bring? Since mood affects performance and well-being, the answers to these questions matter greatly to anyone concerned with public policy. The web is awash with material indicative of public mood, collective forecasting and personal relics. Several efforts have been undertaken to assess emotional status from online sources such as blogs, emails, web sites (Balog & De Rijke 2006) and search engine queries (see, for example, Google Trends). However, these efforts are limited, by the nature of their source material, to hindsight and near-present observations. The work presented here is concerned with collective speculations about the future. We present a visual analysis of publicly available textual content from, a popular web service that allows its users to send themselves emails to be delivered at a later date, up to 30 years in the future. Many of these emails resemble "confessional" time capsules: their content is intended to project the user’s present emotional state at the origination date towards the indicated delivery date. These emails fall into two broad categories of content: a) conjectures about the future and b) mementos regarding the present or the past. By aggregating mood indicators extracted from messages directed to future dates, we can thus assess short and long term shifts in the collective emotional perception toward a particular point in the future. This principle is related to "wisdom of crowd" phenomena as observed in finance and prediction markets (Surowiecki 2004). Numerous psychometric instruments to assess individual mood states and monitor their fluctuations over time exist, the most prominent of which is the 65 item Profile of Mood States (POMS) questionnaire (McNair, Loor, & Droppleman 1971). The 6 dimensional factor analytical structure of the POMS (tension, depression, anger, vigor, fatigue and confusion) has been validated repeatedly (Norcross, Guadagnoli, & Prochaska 2006) and applied in hundreds of studies since its inception (McNair, Heuchert, & Shilony 2003). To make the POMS questionnaire applicable to the open-ended nature of email content, we extended the POMS set of 65 adjectives by nearly 793 synonyms using WordNet and Roget’s Thesaurus. We calculated the occurrences of extended POMS terms in the content of 30,000 publicly available "future" emails and mapped them to a normalized six-dimensional mood vector representing levels of tension, depression, anger, vigor, fatigue and confusion. These mood vectors were grouped according to the delivery date of the original email, resulting in a set of mood state vectors. Statistically significant mood changes were detected especially for depression and vigor indicators. The computation of mood levels was then implemented with a more specific textual analysis of the entire email corpus, aimed at identifying manifestations of conjectures and mementos. The results, presented in this poster, blend two different visual representation of the content analyzed: an "emotional timeline" - a cumulative depiction of mood levels between 2007 and 2036 - and a superimposed topic map of mementos and conjectures - an ontological model of commonly used terms and adjectives illustrating the chains of word association.

Alberto Pepe

and 1 more

Documenting the context in which data are collected is an integral part of the scientific research lifecycle. In field-based research, contextual information provides a detailed description of scientific practices and thus enables data interpretation and reuse. For field data, losing contextual information often means losing the data altogether. Yet, documenting the context of distributed, collaborative, field-based research can be a significant challenge due to the unpredictable nature of real-world settings and to the high degree of variability in data collection methods and scientific practices of different researchers. In this article, we propose the use of microblogging as a mechanism to support collection, ingestion, and publication of contextual information about the variegated digital artifacts that are produced in field research. We perform interviews with scholars involved in field-based environmental and urban sensing research, to determine the extent of adoption of Twitter and similar microblogging platforms and their potential use for field-specific research applications. Based on the results of these interviews as well as participant observation of field activities, we present the design, development, and pilot evaluation of a microblogging application integrated with an existing data collection platform on a handheld device. We investigate whether microblogging accommodates the variable and unpredictable nature of highly mobile research and whether it represents a suitable mechanism to document the context of field research data early in the scientific information lifecycle.