Propaganda in an Age of Algorithmic Personalization: Expanding Literacy Research and Practice

In this commentary, the author considers the rise of algorithmic personalization and the power of propaganda as they shift the dynamic landscape of 21st‐century literacy research and practice. Algorithmic personalization uses data from the behaviors, beliefs, interests, and emotions of the target audience to provide filtered digital content, targeted advertising, and differential product pricing to online users. As persuasive genres, advertising and propaganda may demand different types of reading practices than texts whose purpose is primarily informational or argumentative. Understanding the propaganda function of algorithmic personalization may lead to a deeper consideration of texts that activate emotion and tap into audience values for aesthetic, commercial, and political purposes. Increased attention to algorithmic personalization, propaganda, and persuasion in the context of K–12 literacy education may also help people cope with sponsored content, bots, and other forms of propaganda and persuasion that now circulate online

Measurement of ϒ production in pp collisions at √s = 2.76 TeV

The production of ϒ(1S), ϒ(2S) and ϒ(3S) mesons decaying into the dimuon final state is studied with the LHCb detector using a data sample corresponding to an integrated luminosity of 3.3 pb−1 collected in proton–proton collisions at a centre-of-mass energy of √s = 2.76 TeV. The differential production cross-sections times dimuon branching fractions are measured as functions of the ϒ transverse momentum and rapidity, over the ranges pT < 15 GeV/c and 2.0 < y < 4.5. The total cross-sections in this kinematic region, assuming unpolarised production, are measured to be σ (pp → ϒ(1S)X) × B ϒ(1S)→μ+μ− = 1.111 ± 0.043 ± 0.044 nb, σ (pp → ϒ(2S)X) × B ϒ(2S)→μ+μ− = 0.264 ± 0.023 ± 0.011 nb, σ (pp → ϒ(3S)X) × B ϒ(3S)→μ+μ− = 0.159 ± 0.020 ± 0.007 nb, where the first uncertainty is statistical and the second systematic

Study of the doubly charmed tetraquark T+cc

Quantum chromodynamics, the theory of the strong force, describes interactions of coloured quarks and gluons and the formation of hadronic matter. Conventional hadronic matter consists of baryons and mesons made of three quarks and quark-antiquark pairs, respectively. Particles with an alternative quark content are known as exotic states. Here a study is reported of an exotic narrow state in the D0D0π+ mass spectrum just below the D*+D0 mass threshold produced in proton-proton collisions collected with the LHCb detector at the Large Hadron Collider. The state is consistent with the ground isoscalar T+cc tetraquark with a quark content of ccu⎯⎯⎯d⎯⎯⎯ and spin-parity quantum numbers JP = 1+. Study of the DD mass spectra disfavours interpretation of the resonance as the isovector state. The decay structure via intermediate off-shell D*+ mesons is consistent with the observed D0π+ mass distribution. To analyse the mass of the resonance and its coupling to the D*D system, a dedicated model is developed under the assumption of an isoscalar axial-vector T+cc state decaying to the D*D channel. Using this model, resonance parameters including the pole position, scattering length, effective range and compositeness are determined to reveal important information about the nature of the T+cc state. In addition, an unexpected dependence of the production rate on track multiplicity is observed

Exposure Diversity

The digital environment has fundamentally changed the conditions for media diversity and for exposure diversity in particular, and has made research in this area more important than ever. Paradoxically, the digital information environment, with its abundance of information, has greatly expanded, and at the same time decreased the opportunities for citizens to encounter diverse content. Never was it possible to receive more information, not only from the traditional national media outlets, but also from a myriad of other media companies. And more than ever do citizens rely on the media but also on new institutions such as search engines, social networks and recommendation algorithms to help them filter through the rich choice of information and find and identify relevant and trustworthy information. The objective of this chapter is to identify the main structural, technological and individual challenges for exposure diversity, the state of the art of exposure diversity research so far, and the contours of a future research agenda. In particular, we stress the need for more comparative work, more research that combines normative and empirical expertise, but also work on methodological innovation. We explain why methodological innovations, in the form of online behavior tracking or new forms of observational computational research, can open up new and exciting avenues for answering questions that could not be studied before