Abstract
The article aims to appraise the role of Corporate Social Responsibility (CSR) and innovation strategies as leverages of a company's financial performance. The theoretical and empirical statement of this link aims to reinforce the importance of these strategical options in both the managerial and the public policy domain. Shedding light on the economic return of these practices will help managers make better strategic decisions. Policy makers will also grasp the required evidence to encompass CSR in policy packages. To address the research question, data were collected from the Thomson Reuters Eikon Datastream covering the 1000 largest companies listed on the stock exchange worldwide. Thereafter, hierarchical linear regressions were performed to produce the econometric results. Two time frames (2015-2019) were compared to address time-space trends. Enrolling in CSR activities entails additional costs which can undermine the company's financial performance if not properly supported by public policies. Combining CSR and innovation appears to be the best strategy for companies seeking improvements in their financial performance while being socially responsible. The contribution of this study is threefold: first, the analysis covers the largest thousand firms in operation worldwide; secondly, the econometric results demonstrate that combining CSR with innovation positively impacts financial performance; and lastly, the time comparison evidences a positive but slow evolution in CSR adoption. The article provides an applied perspective, of use both for managers and policy makers, as to how they should approach and disseminate involvement in these types of activities.

Abstract
The paper describes the MetroPT data set, an outcome of a Predictive Maintenance project with an urban metro public transportation service in Porto, Portugal. The data was collected in 2022 to develop machine learning methods for online anomaly detection and failure prediction. Several analog sensor signals (pressure, temperature, current consumption), digital signals (control signals, discrete signals), and GPS information (latitude, longitude, and speed) provide a framework that can be easily used and help the development of new machine learning methods. This dataset contains some interesting characteristics and can be a good benchmark for predictive maintenance models.

Abstract
Time expressions embedded in text are important for many downstream tasks in NLP and IR. They have been, for example, utilized for timeline summarization, named entity recognition, temporal information retrieval, question answering and others. In this paper, we introduce a novel analytical approach to analyzing characteristics of time expressions in diachronic text collections. Based on a collection of news articles published over a 33-years' long time span, we investigate several aspects of time expressions with a focus on their interplay with publication dates of containing documents. We utilize a graph-based representation of temporal expressions to represent them through their co-occurring named entities. The proposed approach results in several observations that could be utilized in automatic systems that rely on processing temporal signals embedded in text. It could be also of importance for professionals (e.g., historians) who wish to understand fluctuations in collective memories and collective expectations based on large-scale, diachronic document collections. © 2022 ACM.

Abstract
The paper presents the Scratch4All project, co-financed by the Portuguese Social Innovation Mission Structure, namely the presentation of the methodology applied in the impact assessment of the first year of the project. A project that uses Scratch software to teach programming languages to fourth grade students (elementary school). Based on the defined indicators, on the characteristics of the beneficiaries and on the activities implemented, adequate measurement instruments were developed to verify the impacts on the target audience. Using secondary and primary sources, indicators were developed to measure the level of change that occurred in each project beneficiary, using quantitative tools. Regarding the software used, Scratch, it was possible to perceive that it enables greater group work skills, working on current social issues and/or technological profiles, fosters greater responsibility in the use of technologies, within the scope of digital citizenship, generates an increase in creativity and innovation, greater willingness to investigate and research different topics, greater communication and collaborative work. © 2022 IEEE Computer Society. All rights reserved.

Abstract
Hashtags are commonly used in social media communication not only to categorize conversations but particularly to raise attention and generate debate of certain topics. Hashtag activism is one of the areas that is gaining particular attention from academics and the overall society. The focus of this chapter is hashtag attributes. Particularly, it analyses and compares four hashtags related to violence against women that circulated on social networks during the COVID-19 pandemic: #16Days, #IsolatedNotAlone, #womensupportingwomen, and #NiUnaMenos. The chapter highlights important aspects to increase the effectiveness of communication with the use of hashtags.

Abstract
Ever since the arrival of streaming platforms, society has become more focused on understanding how to take the next step forward in terms of innovation. Streaming is now a new reality that is growing by the second, and businesses have begun to spend more money on streaming services in order to adapt and improve their products for this new era. This is also the case of Disney+, released at the end of 2019, which had an immediate unexpected growth upon its launch. In comparison to other streaming platforms, Disney+ had an easier debut because of its wide range of unique material available to watch. This study explores Disney+ as a brand, a streaming platform, its features and how they compare to others, as well as the company's business model and revenue, all of which contributed to Disney+ 's current position among other streaming platforms. Regarding Disney+, a survey with 84 responses was conducted, and the results were analysed using descriptive and inferential (chi-square independence test) statistics. As the value of the calculated test statistic (11.24) (chi-square test) is higher than the value in the chi-square table, we conclude that there is a statistically significant association between age and being influenced by advertising.