Month: November 2022

Measuring exposure to misinformation from political elites on Twitter

Mohsen Mosleh & David G. Rand
Nature Communications volume 13, Article number: 7144 (2022)

Misinformation can come directly from public figures and organizations (referred to here as “elites”). Here, we develop a tool for measuring Twitter users’ exposure to misinformation from elites based on the public figures and organizations they choose to follow. Using a database of professional fact-checks by PolitiFact, we calculate falsity scores for 816 elites based on the veracity of their statements. We then assign users an elite misinformation-exposure score based on the falsity scores of the elites they follow on Twitter. Users’ misinformation-exposure scores are negatively correlated with the quality of news they share themselves, and positively correlated with estimated conservative ideology. Additionally, we analyze the co-follower, co-share, and co-retweet networks of 5000 Twitter users and find an ideological asymmetry: estimated ideological extremity is associated with more misinformation exposure for users estimated to be conservative but not for users estimated to be liberal. Finally, we create an open-source R library and an Application Programming Interface (API) making our elite misinformation-exposure estimation tool openly available to the community. Misinformation online can be shared by major political figures and organizations. Here, the authors developed a method to measure exposure to information from these sources on Twitter, and show how exposure relates to the quality of the content people share and their political ideology.

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ALIFE 2023: The International Conference on Artificial Life. Sapporo – Japan, 24th-28th July 2023.

Conference Theme: Ghosts in the machine
Artificial life seeks to unravel the mysteries of life and mind, to naturalise the “ghosts in the machine”. What is life? What is the mind? Are these two concepts related?

These ghosts are however elusive, and difficult to identify or even just define at times. To try and learn more about the mind, research in artificial life and other related fields has more recently focused on studies of complexity, emergence, agency, autonomy, or information theory. As a results, this has led to major advancements in robotics, synthetic biology and artificial intelligence, among others. The main research programs in these areas however seem to be simply forgetting about the mind, rather than trying to explain it.

At the same time, with the advent of new technologies such as brain-machine interface, cyborgization, virtual/augmented reality and the metaverse, the boundaries between agents/living organisms and their environment have began fluctuating. Minds are no longer in our (living organism) shells, expanding beyond current spatial boundaries and into a new form of the “extended mind” hypothesis. At ALIFE 2023, we will bring back the focus to studies of the mind, facing the challenges and embracing the opportunities that come with studies of an often neglected but ever so important concept in both artificial life research and our daily lives.

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End Times: Elites, Counter-Elites, and the Path of Political Disintegration – by Turchin, Peter

From the pioneering co-founder of cliodynamics, the ground-breaking new interdisciplinary science of history, a big-picture explanation for America’s civil strife and its possible endgames

Peter Turchin, one of the most interesting social scientists of our age, has infused the study of history with approaches and insights from other fields for over a quarter century. End Times is the culmination of his work to understand what causes political communities to cohere and what causes them to fall apart, as applied to the current turmoil within the United States.

Back in 2010, when Nature magazine asked leading scientists to provide a ten-year forecast, Turchin used his models to predict that America was in a spiral of social disintegration that would lead to a breakdown in the political order ca 2020. The years since have proved his prediction more and more accurate, and End Times reveals why.

The lessons of world history are clear, Turchin argues: when the equilibrium between ruling elites and the majority tips too far in favor of elites, political instability is all but inevitable. Since the start of the industrial era, this imbalance has been caused not by excessive population growth but by phase shifts of technological innovation and globalization.

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Statistical inference links data and theory in network science

Leto Peel, Tiago P. Peixoto & Manlio De Domenico 
Nature Communications volume 13, Article number: 6794 (2022)

The number of network science applications across many different fields has been rapidly increasing. Surprisingly, the development of theory and domain-specific applications often occur in isolation, risking an effective disconnect between theoretical and methodological advances and the way network science is employed in practice. Here we address this risk constructively, discussing good practices to guarantee more successful applications and reproducible results. We endorse designing statistically grounded methodologies to address challenges in network science. This approach allows one to explain observational data in terms of generative models, naturally deal with intrinsic uncertainties, and strengthen the link between theory and applications.

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An Oncospace for Human Cancers

Aguadé-Gorgorió, G.; Costa, J.; Solé, R. An Oncospace for Human Cancers. Preprints 2022, 2022110211

Human cancers comprise an heterogeneous array of diseases with different progression patterns and responses to therapy. However, they all develop within a host context that constraints their natural history. As it occurs with the diversity of organisms, one can conjecture that there is order in the cancer multiverse. Is there a way to capture the broad range of tumor types within a space of the possible? Here we define the oncospace, a coordinate system that integrates the ecological, evolutionary and developmental components of cancer complexity. The spatial position of a tumor results from its departure from the healthy tissue along these three axes, and progression trajectories inform about the components driving malignancy across cancer subtypes. We postulate that the oncospace topology encodes new information regarding tumorigenic pathways, subtype prognosis and therapeutic opportunities: treatment design could benefit from considering how to nudge tumors towards empty evolutionary deserts in the oncospace.

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