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Social media can contribute to an inclusive society, but they are also asymmetrical and polarised communication spaces. This requires competent teachers to build critical digital citizenship. The aim of this article is twofold: to present web scraping and text analytics as tools that define teachers' digital competences, and to investigate which posts on Twitter and Instagram are most viral in relation to education, disability and inclusion. A total of 48,991 publications in Spanish and English were analysed, corresponding to the period from 13 October 2021 to 1 May 2022. The 100 most viral posts were selected, and correlations were identified between the sentiment, gender and influence associated with the content, its temporal and geographic space. The results show that economic and political influence groups are the most viral, relegating non-profit organisations or individuals with altruistic outreach to second place; only on international days is this trend reversed. Bots do not interfere to impose messages; it is artificial intelligence algorithms that overshadow vindictive and humanistic content. The most influential people are predominantly male, associated with institutional accounts in the political sphere. It is concluded that Big Data and Business Intelligence tools help teachers to analyse relevant educational and social issues, and to acquire a collective ethic in the face of new educational challenges.

Founded in 2006, Zillow established itself as the leading online real estate marketplace. In 2018, Zillow launched Zillow Offers, a new business that purchased and sold homes. Zillow Offers provided home sellers with a faster purchase process than traditional realtors by gathering data from sellers online and making offers immediately, a process known as "iBuying" (i.e., "Instant Buying"). Though new to iBuying, Zillow quickly established a goal of generating $20 billion in annual revenue within three-to-five years. Zillow believed that its artificial intelligence/machine learning (AI/ML) platform for predicting home values, aka "Zestimate," could be a competitive advantage in the iBuying marketplace. However, after losing $421 million in its iBuying business during the third quarter of 2021, the company closed this once-promising business unit rather than risk further losses. CEO Rich Barton asserted that the AI's inability to accurately predict home prices caused the failure of its iBuying business. This case study examines the trajectory of Zillow Offers and discusses several factors that contributed to its demise. After exploring the challenges of its home-price prediction algorithms within iBuying, we argue that the failure of Zillow Offers extends beyond the limitations of its initial AI/ML system. Zillow Offers' focus on hypergrowth over profitability led to operational changes that failed to balance estimated price predictions and operational purchase price decisions. Through this analysis, we raise important questions for students and practitioners about the appropriate and effective use of data-driven AI/ML models for operational decision making.

Over the past few years, academics have undertaken initiatives to bridge the gap between theory and practice in the ever-growing field of business analytics, including implementing real-life student projects in all shapes and forms. Every year since 2015, Manhattan College has invited student teams from across North America and elsewhere in the world to its campus in order to participate in an intercollegiate business analytics competition (BAC@MC). This well-received event and the objectives behind it are described in this article. The program is shown to serve as an effective experiential learning adventure for the undergraduate students as it hones their data analytic skills in the context of an engaging real-world business problem. The roles various stakeholders play in this high-impact practice are highlighted. Furthermore, an example of a recent competition question is presented (along with a summary of the analytical approaches attempted) by the student teams. Descriptive visualizations, regression, and cluster algorithms implemented using python, R, Excel, or Tableau are among the typical analyses utilized by participating students. As witnessed by the students, faculty advisors, and the industry practitioners who attended the event, competitions such as BAC@MC can be rewarding, community-building, and transformative experiences for undergraduate students who will soon become tomorrow's business analysts.

In negotiating to obtain a sample of records from a computer file, it is important to be able to present a simple program that will produce a representative and valid sample. This article describes two procedures: (1) an interval selection method; and (2) a random numbers file. (JAZ)

Changes in our informational environment have brought new challenges and opportunities to address systemic issues of information inequity. Thus, when addressing systemic issues of information inequity, it is important to address it not only from the perspective of information access, as it is often considered in information science, but also from the perspective of how information objects are constructed and produced. This essay brings concerns within information science into discussion with journalism studies and critical technology studies to consider: (1) how the production of information, through the case of mainstream journalism, can create information inequity within information representations, and (2) how the dissemination and retrieval of this journalistic information through algorithmically‐mediated online information systems, specifically social media and search platforms, can replicate and reinforce information inequity within a larger information ecosystem. Thus, this essay uses an interdisciplinary lens to suggest new approaches to holistically address information inequity, putting forth a conceptual framework with actionable steps to create a more equitable information ecosystem. [ABSTRACT FROM AUTHOR]

Given the widespread contribution of independent contractors to organizational innovation and competitive advantage, it is timely to reassess assumptions about the HRM practices appropriate to their management and the rationale for organizations to work with them. In the original and highly influential HR architecture model of Lepak and Snell (1999), contractor status is viewed as an outcome of the low value and/or low uniqueness of human capital resulting in the proposition to externalize and manage them using either none or minimal compliance‐based HRM practices. Developments in digital technologies and algorithmic management epitomized by online labor platforms prompt us to reconsider these assumptions and to challenge the proposed links between value/uniqueness of human capital, employment mode and HRM practices that are assumed by the HR architecture model. Using insights from online labor platforms, we argue that the significant benefits to firms of working with contractors, coupled with the possibilities offered by algorithmic management to efficiently monitor and regulate their behavior, provide a compelling reason for organizations to choose external employment modes even when workers are key to value creation. We challenge the alignment and stability of the relationships proposed by the HR architecture model, and offer propositions to extend the model by reconsidering the rationale for, and nature of, HRM practices associated with contractors. This reassessment is both timely and relevant given the growing prominence of business models where externalizing workers is central alongside the development of new forms of algorithmic human resource management to control them. [ABSTRACT FROM AUTHOR]

The article focuses on the evolution of social media since 2017, highlighting the emergence of platforms like TikTok and the shift towards video content, along with changes in user behavior and engagement rates. Topics include the importance of aligning social media presence with audience demographics, the rise of short-form video content, and strategies for optimizing social media efforts through value-driven content creation and community engagement.

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