Cookies Policy
The website need some cookies and similar means to function. If you permit us, we will use those means to collect data on your visits for aggregated statistics to improve our service. Find out More
Accept Reject
  • Menu
Publications

2023

The Influence of Social Media on Voters’ Decision-Making Process in Portugal: A Case Study

Authors
Garcia J.E.; Vega E.G.; Purificação P.; Fonseca M.J.;

Publication
Smart Innovation, Systems and Technologies

Abstract
Nowadays, social media are inevitably part of people's daily lives. Thus, political communication should also go through digital communication channels, particularly on social media. In such channels, it is important to define a digital marketing and communication strategy to attract new voters and consecutively more votes. As in offline communication channels and also in digital communication, one of the indispensable points in political communication is the candidate’s image. This image must show its own style and differentiate the candidate from his opponents. The main objective of this study is to understand the influence of social media on Portuguese voters’ decision-making process. Throughout the study, different research questions were also analyzed to access which social media are the most used to follow the online political campaign and which criteria influence the voting decision-making process. To achieve this purpose, exploratory research was carried out through questionnaire surveys. Three surveys were conducted based on the Portuguese presidential elections of January 24, 2021. The surveys were distributed before, during, and after the end of the electoral campaign, and 106 people were questioned and answered all 3 surveys. With the results of this study, it was possible to conclude that only 11% of respondents changed their voting intention due to the political communication made by political parties on social media during this electoral campaign. The social media most used by respondents was Facebook, which is also the one they consider the safest and most trustworthy to follow political communication in online media.

2023

Impact in Software Engineering Activities After One Year of COVID-19 Restrictions for Startups and Established Companies

Authors
Hooshyar, H; Guerra, E; Melegati, J; Khanna, D; Aldaeej, A; Matturro, G; Zaina, LAM; Greer, D; Rafiq, U; Chanin, R; Wang, X; Garbajosa, J; Abrahamsson, P; Khomh, F; Duc, AN;

Publication
IEEE Access

Abstract

2023

Green Cosmetics: Determinants of Purchase Intention

Authors
Rodrigues, AC; Pires, PB; Delgado, C; Santos, JD;

Publication
Handbook of Research on Achieving Sustainable Development Goals With Sustainable Marketing

Abstract
This study examined the determinants of purchase intention of green cosmetics, and eight semi-structured interviews were performed to identify them. The determinants identified were environmental awareness, lifestyle, willingness to pay, ethical issues and social and economic justice, cosmetic quality, concern with health, certification labels, trust in the brand, and advertising. Environmental awareness, lifestyle, willingness to pay, quality issues, ethics, and social and economic justice, as well as quality expectations, health concerns, and product knowledge, are the most significant determinants in the intention to purchase green cosmetics. Determinants such as certification labels, brand trust, and advertising are less significant. The research is relevant for the cosmetics industry and its brands to adapt their strategy and product offering to meet consumers’ needs and increase the consumption of green cosmetics and can also serve as a basis for the development of new quantitative studies on the purchase intention of green cosmetics. © 2023 by IGI Global.

2023

Bayesian Federated Learning: A Survey

Authors
Cao, LB; Chen, H; Fan, XH; Gama, J; Ong, YS; Kumar, V;

Publication
PROCEEDINGS OF THE THIRTY-SECOND INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, IJCAI 2023

Abstract
Federated learning (FL) demonstrates its advantages in integrating distributed infrastructure, communication, computing and learning in a privacy-preserving manner. However, the robustness and capabilities of existing FL methods are challenged by limited and dynamic data and conditions, complexities including heterogeneities and uncertainties, and analytical explainability. Bayesian federated learning (BFL) has emerged as a promising approach to address these issues. This survey presents a critical overview of BFL, including its basic concepts, its relations to Bayesian learning in the context of FL, and a taxonomy of BFL from both Bayesian and federated perspectives. We categorize and discuss client- and server-side and FLbased BFL methods and their pros and cons. The limitations of the existing BFL methods and the future directions of BFL research further address the intricate requirements of real-life FL applications.

2023

Precision maturation assessment of grape tissues: Hyperspectral bi-directional reconstruction using tomography-like based on multi-block hierarchical principal component analysis

Authors
Tosin, R; Monteiro-Silva, F; Martins, R; Cunha, M;

Publication
BIOSYSTEMS ENGINEERING

Abstract
This paper introduces a tomography-like method for assessing grape maturation. It analyses inner tissue spectra through point-of-measurement (POM) sensing. A multi-block hierarchical principal component analysis (MHPCA) algorithm was used for the spectral reconstruction of total grapes (skin, pulp, and seed). Two grape cultivars, Loureiro (white; n = 216) and Vinhao (red; n = 205) were measured at 12 dates after veraison (DAV). The reconstructed spectra showed no significant differences (p < 0.001) from the originals for both grapes. Loureiro had better statistical metrics (Person's correlation coefficient (r) values for: total grape: 0.99, skin: 1; pulp: 1, seed: 0.94) than Vinhao (r values for: total grape: 0.92, skin: 0.92; pulp: 0.95, seed: 0.95). Using self learning artificial intelligence (SL-AI), the following parameters were predicted for both grapes: soluble solids content (%; MAPE <13%), puncture force (N; MAPE <29%), chlorophyll content (a.u.; MAPE <29%), and anthocyanin content (a.u.; MAPE <17%, Vinhao only). When comparing observed values with predicted skin, pulp, and seed spectra, Vinhao showed no statistical differences for most parameters, except pulp chlorophyll on one DAV in the final maturation stage. The same was done with the Loureiro cultivar. Although Loureiro mostly showed no statistical differences in assessed parameters across tissues and dates, variations were found in pulp and skin chlorophyll content and puncture force. This tomography-like approach based on tissue maturation can help viticulturists to access instant data on grape maturation, supporting informed decision-making and promoting more sustainable agricultural practices.

2023

Interactive Data Visualizations for Teaching Civic Statistics

Authors
Ridgway, J; Campos, P; Nicholson, J; Teixeira, S;

Publication
Statistics for Empowerment and Social Engagement: Teaching Civic Statistics to Develop Informed Citizens

Abstract
How might you use data visualisation in your teaching? Here, we offer some ideas, and some provocations to review your teaching. We begin with an invitation to examine some of the historical landmarks in data visualisation (DV), to classify the data presented, and to describe the benefits of a sample of the DV to users. Early uses of DV by Nightingale and Neurath are shown, to provide examples of DV which communicated the need for action, and provoked social change. A number of modern DVs are presented, categorised as: tools to display individual data sets and tools for the exploration of specific rich data sets. We argue that students introduced to the core features of Civic Statistics can acquire skills in all of the facets of Civic Statistics set out in Chap. 3. We conclude by revisiting Herschel, to provoke thoughts about the balance of activities appropriate to statistics courses. © Springer Nature Switzerl and AG 2022.

  • 644
  • 4584