On the latest "Stress Test": Is this really Trump's closing message? With the midterms less than a week away, the closing stretch of the campaign is full of bad omens for MAGA abroad and peak weirdness at home. In Serbia and Brazil, Trump allies suffered stinging and surprising defeats driven in part by energized voter turnout. An anti-corruption youth movement spearheaded the surge in Serbia, while Brazil saw a dramatic comeback for President Luiz Inácio Lula da Silva, who defeated staunch Trump ally Flávio Bolsonaro. "Both of the losing candidates, Bolsonaro in Brazil and Vučić in Serbia, wrapped themselves around Donald Trump," co-host David Corn says on this episode of . "So we see in Serbia and Hungary authoritarian figures who try to emulate and ride the Trump wave being tossed out of office. And in [South America], where we've seen a right-wing tide they beat it back" in Brazil. There's a growing sense that voters worldwide are fed up with government grift. As David puts it: "Corruption seems to be the point of the spear." Meanwhile, the Israeli election--where the final results are still uncertain--also was something of a referendum on Trump, with Prime Minister Benjamin Netanyahu attempting to retain power by promoting his close ties to Trump. Back home, former President Barack Obama and Trump were each on the campaign trail in closing sprints. Obama is getting spicy, hitting Trump on his tacky taste and alleged corruption. Trump, meanwhile, has been obsessively commenting on physical anatomy--specifically "asses"--in one of the stranger closing arguments in modern American political history. "This has to be, like, the definition of being off message," co-host Garrison Hayes observes. Trump's fixation on rear-ends extended to rapper Nicki Minaj, who appeared at a rally, where Trump asked her to stand and extolled her derriere, fueling the silly rumor she might be named press secretary after the brief tenure of Katie "Half a Scaramucci" Zacharia."It For Garrison, the gambit is all-too familiar: "Here we are in the closing moments of this midterm election, and the way that the Trump administration has decided to utilize a Black person in order to, I imagine, appeal to Black voters is offensive.

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'This is an apartheid regime' Does Trump have real leverage over Netanyahu? Bots, deepfakes and surveillance: Israel's election goes to war online Share Bots, deepfakes and surveillance: Israel's election goes to war online on social media Polls show the blocs linked to Israeli Prime Minister Benjamin Netanyahu and the opposition, led by former Chief of Staff Gadi Eisenkot, are locked in a virtual tie before Tuesday's general election. Efforts to mobilise supporters, win voters and attack opponents are being played out online through a series of social media advertisements and doctored AI videos. Many of these paint a bleak vision, the outcome depending on whether the party is on the right or centre, of Israel if their rivals win. Both camps are pushing AI-generated and deepfake videos on X.

Is the war entering a new phase? Polls have closed in Russia's first wartime parliamentary elections, with the ruling United Russia party on course to win the tightly controlled vote. The Kremlin wants the elections, the first parliamentary vote since the start of the full-scale invasion of Ukraine in 2022, to showcase popular support for the war and legitimise its action. The drone strikes on Sunday killed at least three people in the Moscow region and two more in the Russian-held part of Ukraine's Kherson region, including an election official, according to the region's governor and the election commission. Russian authorities also reported attacks on the country's electronic voting systems and communication lines during the polls, but said the electoral process was mostly smooth.

Political consultant Bradley Tusk has spent a fortune on mobile voting efforts. Now, he's launching a protocol to try to mainstream the technology. Joe Kiniry, a security expert specializing in elections, was attending an annual conference on voting technology in Washington, DC, when a woman approached him with an unusual offer. She said she represented a wealthy client interested in funding voting systems that would encourage bigger turnouts. Did he have any ideas?

Online social networks have transformed the ways in which political mobilization messages are disseminated, raising new questions about how peer influence operates at scale. Building on the landmark 61-million-person Facebook experiment \citep{bond201261}, we develop an agent-based simulation framework that integrates real U.S. Census demographic distributions, authentic Twitter network topology, and heterogeneous large language model (LLM) agents to examine the effect of mobilization messages on voter turnout. Each simulated agent is assigned demographic attributes, a personal political stance, and an LLM variant (\texttt{GPT-4.1}, \texttt{GPT-4.1-Mini}, or \texttt{GPT-4.1-Nano}) reflecting its political sophistication. Agents interact over realistic social network structures, receiving personalized feeds and dynamically updating their engagement behaviors and voting intentions. Experimental conditions replicate the informational and social mobilization treatments of the original Facebook study. Across scenarios, the simulator reproduces qualitative patterns observed in field experiments, including stronger mobilization effects under social message treatments and measurable peer spillovers. Our framework provides a controlled, reproducible environment for testing counterfactual designs and sensitivity analyses in political mobilization research, offering a bridge between high-validity field experiments and flexible computational modeling.\footnote{Code and data available at https://github.com/CausalMP/LLM-SocioPol}

Perpetual voting considers sequences of decis ions made by the same electorate, where fairness must be evaluated over time rather than perdecision [16]. A centralchallenge in this setting is ensuring adequaterepresentation for voters who are repeatedly in the minority. Traditional a ggregation rules, such as majority voting or Borda count, fail in this regard: they offer no guarantees of long-term fai rness or cumulative influence. In response, methods such as Perpetual Phragmén [17] and Perpetual Consensus [16] hav e been proposed to distribute influence more equitably over time. However, they rely on full knowledge of all voters ' approval sets, implicitly requiring consistent voter participation, a condition which can be hard to satisfy in real-world contexts. Real-world elections face various practical constraints-- including scheduling conflicts, limited resources, and restricted information access--that inevitably prevent vote rs from participating consistently.

Large language models (LLMs) are perceived by some as having the potential to revolutionize social science research, considering their training data includes information on human attitudes and behavior. If these attitudes are reflected in LLM output, LLM-generated "synthetic samples" could be used as a viable and efficient alternative to surveys of real humans. However, LLM-synthetic samples might exhibit coverage bias due to training data and fine-tuning processes being unrepresentative of diverse linguistic, social, political, and digital contexts. In this study, we examine to what extent LLM-based predictions of public opinion exhibit context-dependent biases by predicting voting behavior in the 2024 European Parliament elections using a state-of-the-art LLM. We prompt GPT-4-Turbo with anonymized individual-level background information, varying prompt content and language, ask the LLM to predict each person's voting behavior, and compare the weighted aggregates to the real election results. Our findings emphasize the limited applicability of LLM-synthetic samples to public opinion prediction. We show that (1) the LLM-based prediction of future voting behavior largely fails, (2) prediction accuracy is unequally distributed across national and linguistic contexts, and (3) improving LLM predictions requires detailed attitudinal information about individuals for prompting. In investigating the contextual differences of LLM-based predictions of public opinion, our research contributes to the understanding and mitigation of biases and inequalities in the development of LLMs and their applications in computational social science.

This information was projected on the life cycle of the Their distributed communicating nature makes them vulnerable turnout according to time aging and operation aging to cyberattacks [2]. The security of CPS has criteria in order to compute a cyberthreat likelihood for emerged as a complex problem, after discovering the each current curve observed. Maintenance operators use Stuxnet malware [3] that targeted the Iranian industrial the estimated likelihood to assess the authenticity of each control system.

Former Wisconsin Gov. Scott Walker, R., joined Americas Newsroom to discuss what is at stake with the swing states pivotal election. A Wisconsin woman is using online dating applications to reach young people nationwide and help raise voter turnout during elections, according to a local report. Kristi Johnston is part of Next Gen. America, an organization that works toward increasing voter turnout among young Americans, WKOW-TV reported. Johnston and the group do not push for any specific political party or candidate and instead raise awareness and remind people to get out and vote.