1,104 research outputs found
The vanishing author in computer-generated works: a critical analysis of recent Australian case law
No full textAbstract
The use of software is ubiquitous in the creation of many copyright works, yet the requirement in copyright law that every work have a human author who engages in independent intellectual effort means that its use may prevent copyright subsistence. Several recent Australian cases have refocused attention on authorship as an essential criterion of copyright subsistence, and these cases suggest that much computer-produced output may be authorless and thus lack copyright protection. This article, the first in a two-part series, analyses how each case deals with the question of authorship of computer-produced works and why the use of software diminishes copyright protection for a significant number of computer-generated works. The article critiques the application of conventional notions of human authorship developed in the pre-computer age to modern productions and suggests alternative approaches to authorship that satisfy both the major objectives of copyright policy and the need to adapt to the computer age. The article argues that, without a broader judicial approach to authorship of computer-generated works, Parliament must remedy the lacuna in protection for these ‘authorless’ works. Possible solutions for reform are suggested. In a forthcoming article, the author comprehensively examines those reform proposals
Comparison of Cluster Analysis Approaches for Binary Data
No full textCluster methods allow to partition observations into homogeneous groups. Standard cluster analysis approaches consider the variables used to partition observations as continuous. In this work, we deal with the particular case all variables are binary. We focused on two specific methods that can handle binary data: the monothetic analysis and the model-based co-clustering. The aim is to compare the outputs performing these two methods on a common dataset, and figure out how they differ. The dataset on which the two methods are performed is a UNESCO dataset made up of 58 binary variables concerning the ability of UNESCO management to use Internet to promote world heritage sites
Price indicators for Airbnb accommodations
No full textNew forms of hospitality grew increasingly more popular and successful during the last decades. Nowadays, they are chosen for different reasons, one of the most important certainly being price. Understanding the elements that can impact on price determination is crucial to increase profitability. We propose two price indicators for Airbnb accommodations, which are defined in three phases using proportional odds model as a reference model. The first phase focuses on the probability estimation of accommodations belonging to a specific class of price. The second phase aims to evaluate the ability of the model to make good predictions by computing three different indexes. Finally, the three indexes are combined to define the indicators q and r which evaluate, respectively, the impact that six different dimensions (transports, culture, crowd, property, management, and time) have with respect to price determination on Airbnb accommodations and their relative importance concerning neighborhoods. The analysis is focused on 61 neighborhoods of Rome. The findings show differences with respect to the impact of the dimensions on price for each neighborhood of Rome
First person – Viorica Raluca Contu
No full textABSTRACT
First Person is a series of interviews with the first authors of a selection of papers published in Journal of Cell Science, helping early-career researchers promote themselves alongside their papers. Viorica Raluca Contu is co-first author on ‘Lysosomal targeting of SIDT2 via multiple YxxΦ motifs is required for SIDT2 function in the process of RNautophagy’, published in Journal of Cell Science. Viorica is a PhD student at the National Institute of Neuroscience, NCNP, Japan, investigating intracellular RNA degradation by the lysosomes and its possible involvements in disease pathogenesis and treatment.</jats:p
VGLM proportional odds model to infer hosts’ Airbnb performance
No full textWe investigated aspects of host activities that influence and enhance host performance in an effort to achieve best results in terms of the occupancy rate and the overall rating. The occupancy rate measures the percentage of reserved days with respect to available days. The overall rating identifies the satisfaction level of guests that booked an Airbnb accommodation. We used the proportional odds model to estimate the impact of the managerial variables and the characteristics of the accommodation on host performance. Five different levels of the occupancy and the overall rating were investigated to understand which features impact them and support the effort to move from the lowest to the highest level. The analysis was carried out for Italy’s most visited cities: Rome, Milan, Venice, and Florence. We focused on the year 2016. Moreover, we investigated different impact levels in terms of the overall rating during the COVID-19 pandemic to evaluate possible differences. Our findings show the relevance of some variables, such as the number of reviews, services, and typology of the rented accommodation. Moreover, the results show differences among cities and in time for the relevant impact of the COVID-19 pandemic
Topic based quality indexes assessment through sentiment
No full textThis paper proposes a new methodology called TOpic modeling Based Index Assessment through Sentiment (TOBIAS). This method aims at modeling the effects of the topics, moods, and sentiments of the comments describing a phenomenon upon its overall rating. TOBIAS is built combining different techniques and methodologies. Firstly, Sentiment Analysis identifies sentiments, emotions, and moods, and Topic Modeling finds the main relevant topics inside comments. Then, Partial Least Square Path Modeling estimates how they affect an overall rating that summarizes the performance of the analyzed phenomenon. We carried out TOBIAS on a real case study on the university courses’ quality evaluated by the University of Cagliari (Italy) students. We found TOBIAS able to provide interpretable results on the impact of discussed topics by students with their expressed sentiments, emotions, and moods and with the overall rating
From self-perception to feedback: mapping sustainability-oriented self-descriptions to Airbnb reviews
No full textUnderstanding the relationship between self-perception and online feedback is crucial for assessing behavioral consistency in sustainability-oriented consumers. This study examines whether Airbnb users who describe themselves using sustainability-related
terms reflect similar concerns in their reviews. We first filter user self-descriptions based
on sustainability-related keywords and apply topic modeling to both self-descriptions and reviews. To analyze the relationship between self-reported identity and review content, we employ a chi-squared independence test on the dominant topics of self-descriptions and reviews. Additionally, we assess the association between the dominant self-description topic and the dominant emotion expressed in reviews. Our findings provide insights into the extent to which self-declared sustainability orientations influence user-generated content, oering implications for consumer behavior analysis and sustainability communication in online platforms
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