Any report frames issues to favor a particular interpretation by highlighting or excluding certain aspects of a story. Despite the widespread use of framing in disinformation, framing properties and detection methods remain underexplored outside the English-speaking world. We explore how multilingual framing of the same issue differs systematically. We use eight years of Russia-backed disinformation campaigns, spanning 8k news articles in 4 languages targeting 15 countries. We find that disinformation campaigns consistently and intentionally favor specific framing, depending on the target language of the audience. We further discover how Russian-language articles consistently highlight selected frames depending on the region of the media coverage. We find that the two most prominent models for automatic frame analysis underperform and show high disagreement, highlighting the need for further research.

NATO leaders are holding their annual summit as Ukraine looks to the security alliance for support in its attempt to push back invading Russian forces. The Vilnius communique, however, while emphasising NATO's support for Ukraine, gave no clear timetable on when the country might be able to join the alliance, in a major disappointment for Ukrainian President Volodymyr Zelenskyy, who had travelled to the Lithuanian capital. "Ukraine's future is in NATO," the leaders said in the joint statement on Tuesday. "We will be in a position to extend an invitation to Ukraine to join the alliance when allies agree and conditions are met," the declaration said, without specifying the conditions. The communique also touched on the Asia Pacific, with the leaders of Australia, Japan, New Zealand and South Korea all attending as NATO allies. It said China was a challenge to NATO's interests, security and values with its "ambitions and coercive policies" triggering a furious response from Beijing. And it accused Beijing and Moscow of "mutually reinforcing attempts to undercut the rules-based international order". China has said it wants peace in Ukraine, but has not condemned Russia's full scale invasion since it began in February 2022. NATO is a defensive Alliance. It is the unique, essential and indispensable transatlantic forum to consult, coordinate and act on all matters related to our individual and collective security. We reaffirm our iron-clad commitment to defend each other and every inch of Allied territory at all times, protect our one billion citizens, and safeguard our freedom and democracy, in accordance with Article 5 of the Washington Treaty. We will continue to ensure our collective defence from all threats, no matter where they stem from, based on a 360-degree approach, to fulfil NATO's three core tasks of deterrence and defence, crisis prevention and management, and cooperative security. We adhere to international law and to the purposes and principles of the Charter of the United Nations and are committed to upholding the rules-based international order. This Summit marks a milestone in strengthening our Alliance. We look forward to our valuable exchanges with the Heads of State and Government of Australia, Japan, New Zealand, and the Republic of Korea, as well as the President of the European Council and the President of the European Commission at this Summit. We also welcome the engagements with the Foreign Ministers of Georgia and the Republic of Moldova, and with the Deputy Foreign Minister of Bosnia and Herzegovina, as we continue to consult closely on the implementation of NATO's tailored support measures. This is an historic step for Finland and for NATO. For many years, we worked closely as partners; we now stand together as Allies. NATO membership makes Finland safer, and NATO stronger. Every nation has the right to choose its own security arrangements.

Russia's biggest technology company enjoys a level of dominance that is unparalleled by any one of its Western counterparts. Think Google mixed with equal parts Amazon, Spotify and Uber and you're getting close to the sprawling empire that is Yandex--a single, mega-corporation with its hands in everything from search to ecommerce to driverless cars. But being the crown jewel of Russia's silicon valley has its drawbacks. The country's government sees the internet as contested territory amid ever-present tensions with US and other Western interests. As such, it wants influence over how Yandex uses its massive trove of data on Russian citizens. Foreign investors, meanwhile, are more interested in how that data can be turned into growth and profit. For the September/October issue of MIT Technology Review, Moscow-based journalist Evan Gershkovich explains how Yandex's ability to walk a highwire between the Kremlin and Wall Street could potentially serve as a kind of template for Big Tech.

In this paper, we expand on our previous research of the potential for abuse of generative language models by assessing GPT-3. Experimenting with prompts representative of different types of extremist narrative, structures of social interaction, and radical ideologies, we find that GPT-3 demonstrates significant improvement over its predecessor, GPT-2, in generating extremist texts. We also show GPT-3's strength in generating text that accurately emulates interactive, informational, and influential content that could be utilized for radicalizing individuals into violent far-right extremist ideologies and behaviors. While OpenAI's preventative measures are strong, the possibility of unregulated copycat technology represents significant risk for large-scale online radicalization and recruitment; thus, in the absence of safeguards, successful and efficient weaponization that requires little experimentation is likely. AI stakeholders, the policymaking community, and governments should begin investing as soon as possible in building social norms, public policy, and educational initiatives to preempt an influx of machine-generated disinformation and propaganda. Mitigation will require effective policy and partnerships across industry, government, and civil society.

TBILISI - The speaker of Georgia's parliament stepped down Friday in the wake of violent clashes that left at least 240 people injured, but the move failed to assuage protesters, who returned to the streets demanding that the interior minister also step down over a brutal police response. A night of clashes Thursday was sparked by a Russian lawmaker who took the speaker's seat as a group of international lawmakers met at the Georgian parliament in Tbilisi. It angered the opposition, which sees the current Georgian government as overly friendly to Russian interests. The protests mark the largest outpouring of anger against the ruling Georgian Dream since it took power in 2012. Officials said at least 240 people were injured when riot police fired rubber bullets and tear gas and unleashed water cannon on protesters outside Georgia's parliament building during the clashes that lasted into early Friday.

Foreign policy analysis has been struggling to find ways to measure policy preferences and paradigm shifts in international political systems. This paper presents a novel, potential solution to this challenge, through the application of a neural word embedding (Word2vec) model on a dataset featuring speeches by heads of state or government in the United Nations General Debate. The paper provides three key contributions based on the output of the Word2vec model. First, it presents a set of policy attention indices, synthesizing the semantic proximity of political speeches to specific policy themes. Second, it introduces country-specific semantic centrality indices, based on topological analyses of countries' semantic positions with respect to each other. Third, it tests the hypothesis that there exists a statistical relation between the semantic content of political speeches and UN voting behavior, falsifying it and suggesting that political speeches contain information of different nature then the one behind voting outcomes. The paper concludes with a discussion of the practical use of its results and consequences for foreign policy analysis, public accountability, and transparency.

This week FIFA's senior representative, Tokyo Sexwale, will throw his hat into the ring as he attempts to resolve disagreements between Israeli and Palestinian football associations. The disputes are over Israeli restrictions placed on the movement of Palestinian players and the participation of at least five Israeli football clubs in Israeli leagues - two issues which Palestinians claim contravene FIFA's own rules. While progress has been achieved on movement for Palestinian players, the issue of settlement teams remains intractable. Their inclusion within Israeli leagues is the manifestation of a political process that seeks to normalise Israel's claim to the Palestinian territory it occupied in 1967. In this context, football has become a tool to legitimise the expanding settlements as an integral part of Israel.

Information extraction systems have been recently proposed for organizing and exploring content in large online text corpora as information networks . In such networks, the nodes are named entities (e.g., people, organizations) while the edges correspond to statements indicating relations among such entities. To date, such systems extract rather primitive networks, capturing only those relations which are expressed by direct statements. In many applications, it is useful to also extract more subtle relations which are often expressed as meta statements in the text. These can, for instance provide the context for a statement (e.g., “Google acquired YouTube on October 2006”), or repercussion about a statement (e.g., “The US condemned Russia’s invasion of Georgia”). In this work, we report on a system for extracting relations expressed in both direct statements as well as in meta statements. We propose a method based on Conditional Random Fields that explores syntactic features to extract both kinds of statements seamlessly. We follow the Open Information Extraction paradigm, where a classifier is trained to recognize any type of relation instead of specific ones. Finally, our results show substantial improvements over a state-of-the-art information extraction system, both in terms of accuracy and, especially, recall.