arXiv subjects

Venera Tomaselli

Publications and source records attributed to Venera Tomaselli.

3 recordsLinked to original sources

arXiv2023

Ideology-driven polarisation in online ratings: the review bombing of The Last of Us Part II

A review bomb is a large and quick surge in online reviews about a product, service, or business, coordinated by a group of people willing to manipulate public opinion about that entity. This study challenges the assumption that review bombing is solely a phenomenon of misinformation and connects motivations and substantial content of online reviews with the broader theory of judgement of facts and of value. These theories are verified in a quantitative analysis of the most prominent case of review bombing, which involves the video game The Last of Us Part II. It is discovered that ideology-driven ratings are followed by a grassroots counter-bombing, aimed at mitigating the effects of the negative ratings. The two factions of bombers, despite being politically polar opposites, are very similar in terms of other metrics. Evidence suggests the theoretical framework of political disinformation is insufficient to explain this case of review bombing. In light of the need to re-frame review bombing, recommendations are proposed for the preventive management of future cases.

cs.CY↗

arXiv2022

Hybrid Probabilistic-Snowball Sampling

Snowball sampling is the common name for sampling designs on human populations where respondents are requested to share the questionnaire among their social ties. With some exceptions, estimates from snowball samplings are considered biased. However, the magnitude of the bias is influenced by a combination of elements of the sampling design and features of the target population. Hybrid Probabilistic-Snowball Sampling Designs (HPSSD) aims to reduce the main source of bias in the snowball sample through randomly oversampling the first stage 0 of the snowball. To check the behaviour of HPSSD for applications, we developed an algorithm that, by grafting the edges of a stochastic blockmodel into a graph of cliques, simulates an assortative network of tobacco smokers. Different outcomes of the HPSSD operations are simulated, too. Inference on 8,000 runs of the simulation leads to think that HPSSD does not improve reliability of samples that are already representative. But if homophily in the population is sufficiently low, even the unadjusted sample mean of HPSSD has a slightly better performance than a random, but undersized, sampling. De-biasing the estimates of HPSSD shows improvement in the performance, so an adjusted HPSSD estimator is a desirable development.

stat.CO↗

arXiv2015

Ecological fallacy and covariates: new insights based on multilevel modelling of individual data

This paper deals with the issue of ecological bias in ecological inference. We provide an explicit formulation of the conditions required for the ordinary ecological regression to produce unbiased estimates and argue that, when these conditions are violated, any method of ecological inference is going to produce biased estimates. These findings are clarified and supported by empirical evidence provided by comparing the results of three main ecological inference methods with those of multilevel logistic regression applied to a unique set of individual data on voting behaviour. The main findings of our study have two important implications that apply to all situations where the conditions for no ecological bias are violated: (i) only ecological inference methods that allow to model the effect of covariates have a chance to produce unbiased estimates; (ii) the set of covariates to be included in the model to remove bias is limited to the marginal proportions. Finally, our results suggest that, when the association between two ecological variables is very weak, it is not possible to obtain unbiased estimates even by an appropriate model that accounts for the effect of relevant covariates.

stat.AP↗