This paper presents a longitudinal open dataset of Spanish public procurement extracted from the Official State Gazette (BOE) covering the period 2014-2024. The dataset integrates structured information on contracts, contracting authorities, suppliers, amounts, and procedures, enabling large-scale quantitative analysis of public procurement dynamics in Spain. We describe the data extraction and normalization pipeline, provide descriptive statistical analyses of temporal and sectoral trends, and discuss potential applications in transparency research, public policy evaluation, and computational social science. The dataset is released to facilitate reproducible research on public procurement and government contracting.
BACKGROUND The COVID-19 pandemic has unfolded alongside what the Director-General of the World Health Organization has termed an “infodemic” of misinformation . In their coverage of the pandemic, traditional media outlets have reported and sometimes amplified the voices of various actors across the political spectrum who have advocated unproven cures, denied what is known scientifically about the nature and origins of the novel SARS-CoV-2 coronavirus, and proposed conspiracy theories which purport to explain causation and often allege nefarious intent. These competing narratives and explanations have risen and fallen rapidly, behaving almost as viral phenomena themselves. Misinformation about COVID-19 is a serious threat to global public health. If people are misled by unsubstantiated claims about the nature and treatment of the disease, they are less likely to observe official health advice and may thus contribute to the spread of the pandemic and pose a danger to themselves and others. Health protection strategies such as hygiene, sanitation, social distancing, mask wearing, lockdowns, and other measures will be less effective if distrust of public health authorities becomes sufficiently widespread to substantially affect public behavior. Specifically, misinformation about treatments for COVID disease can prompt people to attempt cures that might harm them, while fears and distrust about a possible vaccine could undermine the uptake of any vaccination campaign aiming to immunize the public at a later date. Both misinformation and disinformation center on the dissemination of false information, with the difference being that the former is shared without malice while the latter is spread with the intent to deceive. Though we use the term misinformation in this study, it is clear that some of the nine main topics that emerged do include elements of disinformation in that they appear to have been shared intentionally, primarily to advance political agendas, and others are a combination of misinformation and disinformation. OBJECTIVE It is commonly assumed that misinformation is largely a phenomenon of social media, provoking calls for stricter regulation of the content on platforms such as Facebook and Twitter. However, misinformation also appears in traditional media. Here it typically takes two forms: amplification of false claims through widespread coverage of prominent persons whose views and comments are considered newsworthy; and to a lesser degree, active fact-checking and debunking of false claims and misinformation. In this paper we aim to quantify the extent of the COVID infodemic within traditional media and examine it as a multi-dimensional informational phenomenon. While previous authors have investigated specific types of social media misinformation , including the role of “bots” in its dissemination , to our knowledge our analysis is the first comprehensive survey of the traditional and online media landscape regarding COVID-19 misinformation, encompassing millions of articles published globally within the five-month span that followed the outbreak of the pandemic in January 2020. Ours is not the first media assessment: the Reuters Institute/Oxford Martin School published a factsheet in April 2020 looking at “Types, Sources and Claims of COVID-19 Misinformation,” but this considered a sample of only 225 misinformation examples in the media . By using a quantitative approach examining a comprehensive English-language global media database of tens of millions of articles, we aim to present empirical insights into the nature and impact of the entire infodemic that may better inform response measures taken by public health authorities, media institutions, governmental organizations, academia, and others. METHODS We performed a comprehensive analysis of media coverage of the COVID-19 pandemic using Cision’s Next Generation Communications Cloud platform. This commercial platform aggregates online news (including licensed print and traditional media news content via LexisNexis), blogs, podcasts, TV, and radio, sourced via webcrawlers and third-party content providers. In total, this database encompasses a network of 7 million-plus global sources of print, broadcast, and online news. Cision’s comprehensive coverage and search capabilities make it a potentially powerful tool for the kind of content analysis we perform here. This Next Generation Communications Cloud database aggregates global coverage, with the largest volume of English-language results coming in descending order from the United States, United Kingdom, India, Ireland, Australia, and New Zealand, with African and other Asian nations also represented in the sample. This database was queried using an English-language search string for misinformation topics in the context of COVID-19. The search string included variations on common thematic keywords (“COVID-19”, “coronavirus”, “2019-nCoV”, etc.) and used Boolean operators such as AND, OR, NOT, and proximity terms to sift for relevant content. (For a full reproduction of Boolean operators see Supplementary Information 1.) Media coverage was examined from a sample of articles published between January 1 and May 26, 2020. Misinformation terms were identified by an iterative cycle of reviewing coverage of COVID-19-related misinformation, creating an initial search string, further reviewing coverage, and adding additional terms to improve inclusiveness. Sites known to produce non-news content, such as wordpress.com and livejournal.com, were excluded. Keyword-based, pre-set content filters for press releases, job postings, earnings and stock news, and other irrelevant categories were applied in order to exclude them from results. Specific misinformation topics were identified within media coverage via a similar iterative approach of reviewing sample coverage, search query adjustment, and further review of coverage until it was possible to determine that the leading misinformation narratives over the time period were represented since new topic searches failed to generate a substantial volume of results. Misinformation topics were then searched within the overarching misinformation search, operating as a layering set of context terms. When topic research identified new misinformation keywords, they were added to the master search to further improve comprehensiveness. There is obviously a distinction to be made between misinformation per se (defined as information that is likely to mislead the audience) and information that discusses misinformation topics or the phenomenon of the infodemic with the explicit objective of debunking or correcting factual inaccuracies. We explicitly isolate this fact-checking coverage within the broader misinformation sample by identifying common terms used to identify misinformation as false, such as “fact-check” and “false claim”, as well as the use of terms like “misinformation" and "conspiracy theory" which inherently imply that the narratives they reference are untrue. Coverage falling into the misinformation search was also compared to coverage of COVID-19 generally, which was defined as the misinformation COVID-19 search excluding misinformation context terms. We quantify the extent of misinformation by volume, meaning the number of articles about a topic. To avoid excluding coverage that mentions more than one topic, topics within the report are not mutually exclusive. A notable amount of overlap between certain topics was observed, thus “frequency” is used to ensure accurate representation of each topic. In this report, “frequency” is defined as the volume of a specific topic divided by the total volume for the misinformation conversation. RESULTS From January 1 to May 26, 2020, English-language traditional media outlets published over 1.1 million individual articles (total 1,116,952) mentioning COVID-19 misinformation. This represented just under 3% of the overall COVID-19 conversation (total 38,713,161 articles) during the same timeframe. We identified five different sub-sections within the overall COVID misinformation conversation, summarized in Table 1. (See Supplementary Info for specific search strings that yielded these results.) Specifically: • Misinformation/conspiracies sub-topics: We identified 11 key sub-topics within this conversation, which are shown in Table 2 and profiled in more detail in the discussion section below. • Trump mentions: This topic comprises all mentions of US President Donald Trump within the total misinformation conversation, irrespective of whether other subjects were also referenced in the same news article. This topic is included as a way to quantify the prominence of Trump within the overall COVID “infodemic” without risking double-counting by combining Trump mentions from a number of topics that can be expected to overlap. Any and all mentions of Trump will appear in this category irrespective of whether they also appear elsewhere. • Infodemic coverage: This topic includes articles that mentioned the general term “infodemic” (or related keywords such as “misinformation” or “hoax” combined with mentions of COVID-19) without mentioning a specific additional topic such as 5G or Dr Fauci. • Fact-checking: This topic includes articles that explicitly mentioned conspiracies, misinformation, or factual inaccuracies in a way that aimed to correct misinformation with the audience. Examples of this coverage include articles from established fact-checking sources, such as The Washington Post's Fact Checker, and coverage that mentioned the fact-checking of COVID-19 misinformation. • Trump-only mentions: This topic represents the volume and frequency of articles that mentioned President Trump in the context of misinformation but did not mention a specific other topic at the same time. Examples were articles alleging in general terms that Trump has spread misinformation about COVID-19 or discus
We introduce SeaLLMs-Audio, the first large audio-language model (LALM) tailored for multiple Southeast Asian (SEA) languages-Indonesian (id), Thai (th), and Vietnamese (vi)-alongside English (en) and Chinese (zh). Trained on a large-scale audio corpus, SeaLLMs-Audio exhibits strong performance across diverse audio-centric tasks, spanning fine-grained audio understanding and voice-based interaction. Its key features include: 1) Multilingual: the model primarily supports 5 languages, namely Indonesian, Thai, Vietnamese, English, and Chinese; 2) Multimodal: the model accepts flexible input modalities, including audio only, text only, as well as audio with text; 3) Multi-task: the model supports a wide range of tasks, including audio analysis tasks such as Audio Captioning, Automatic Speech Recognition, Speech-to-Text Translation, Speech Emotion Recognition, Speech Question Answering, and Speech Summarization. It also enables voice-based dialogue, including answering factual, mathematical, and general knowledge queries. As a significant step towards advancing audio LLMs in Southeast Asia, we expect SeaLLMs-Audio to benefit both the regional research community and industry. To automate LALM evaluation for Southeast Asia, we introduce SeaBench-Audio, a benchmark spanning multiple tasks. Experiments show that SeaLLMs-Audio achieves competitive performance compared with other LALMs on SEA languages.
Large Language Models (LLMs) are increasingly integral to information dissemination and decision-making processes. Given their growing societal influence, understanding potential biases, particularly within the political domain, is crucial to prevent undue influence on public opinion and democratic processes. This work investigates political bias and stereotype propagation across eight prominent LLMs using the two-dimensional Political Compass Test (PCT). Initially, the PCT is employed to assess the inherent political leanings of these models. Subsequently, persona prompting with the PCT is used to explore explicit stereotypes across various social dimensions. In a final step, implicit stereotypes are uncovered by evaluating models with multilingual versions of the PCT. Key findings reveal a consistent left-leaning political alignment across all investigated models. Furthermore, while the nature and extent of stereotypes vary considerably between models, implicit stereotypes elicited through language variation are more pronounced than those identified via explicit persona prompting. Interestingly, for most models, implicit and explicit stereotypes show a notable alignment, suggesting a degree of transparency or "awareness" regarding their inherent biases. This study underscores the complex interplay of political bias and stereotypes in LLMs.
Organized crime groups use coercion, corruption, and collusion with political actors to achieve their aims. Why do organized crime organizations sometimes quietly coexist with local authorities, sometimes collude with them, and at other times threaten or attack them? Once restricted to few areas in advanced democracies, recent literature and media attention have shown how the impact of organized crime on political arenas is spreading across new and old democracies. This article examines how local political and economic conditions shape the strategies that organized crime adopts toward public institutions. We propose a typology of three main strategies—parasitic, collusive, and adversarial—and explore the conditions under which each emerges. Using an original data set covering almost 8000 Italian municipalities, we show that collusion is most likely where weak political parties leave local political systems open to infiltration, while adversarial strategies arise where high levels of public spending make control over resources especially valuable. The analysis demonstrates that criminal behavior is not random but responds to identifiable political and economic incentives. Beyond the Italian case, these findings illuminate how variations in democratic institutions and local economies can foster different forms of organized crime behavior.
Introduction. The period from 1957 to 1963 is an important period in the history of the city of Elista. In 1957 the autonomy of the Kalmyk people was restored, the statute of the capital city of the republic was returned to Elista, and the city itself received a powerful impetus for its further development. Since the city did not have its own resources for reconstruction, financial and other types of material assistance played the main role in this process from the state and population migrations organized by it. The great importance that population migrations had for Elista, the largest city in Kalmykia, makes it necessary to study this aspect in the past life of the city, which, moreover, was not specifically studied. The study aims to highlight the migration policy of the state during the years of the restoration of the republic and the most massive migrations in the history of the city, to show their impact on the development of the city. The article was prepared on the basis of documents of the state authorities of the Kalmyk ASSR, stored in the National Archive of the Republic of Kalmykia. The research was carried out based on historical-comparative and historical-genetic research methods. Results. In 1957–1963, there was a sharp surge in population migrations in Elista, caused by the restoration of Kalmykia as an administrative-territorial entity in 1957 and the granting of the city the legal status of its capital. The state allocated large funds for the restoration and further development of the socio-economic structure of the city, but there was a shortage of personnel and labor resources in general for the development of capital investments. To solve this problem, the authorities attracted Kalmyks returning from places of deportation to the city, conducted recruitment among workers from other subjects, invited military personnel demobilized by their army, and sent graduates of vocational schools to the city. As a result, the shortage of workers was largely overcome, which made it possible in 1964 to abandon new mass organized relocations to the city. Conclusions. The massive influx of population in 1957–1963 had a great impact on the demographic, social and national structure of the population. The population of Elista has increased dramatically, especially among young people, which has improved the demographic indicators of citizens, their social composition has changed, which has transformed into an urban one, the city has turned from a mono-national into a multi-national one.
History of Asia, Political institutions and public administration - Asia (Asian studies only)
Emanuele Musumeci, Michele Brienza, Vincenzo Suriani
et al.
In the last years' digitalization process, the creation and management of documents in various domains, particularly in Public Administration (PA), have become increasingly complex and diverse. This complexity arises from the need to handle a wide range of document types, often characterized by semi-structured forms. Semi-structured documents present a fixed set of data without a fixed format. As a consequence, a template-based solution cannot be used, as understanding a document requires the extraction of the data structure. The recent introduction of Large Language Models (LLMs) has enabled the creation of customized text output satisfying user requests. In this work, we propose a novel approach that combines the LLMs with prompt engineering and multi-agent systems for generating new documents compliant with a desired structure. The main contribution of this work concerns replacing the commonly used manual prompting with a task description generated by semantic retrieval from an LLM. The potential of this approach is demonstrated through a series of experiments and case studies, showcasing its effectiveness in real-world PA scenarios.
Background: This study examines cardiometabolic (CM) risk factors in an urban South Asian population, integrating medical and Anthropological perspectives to explore the effects of socio-economic, lifestyle, gender-specific factors, and cultural norms on health outcomes. Results: Analysis indicates a high prevalence of MetS and Pre-MetS, particularly among females, with significant predictors including BMI, triglycerides, total cholesterol, and waist circumference, alongside socio-genetic and lifestyle factors. Employing Elastic Net logistic regression, the researcher rigorously validated models to evaluate their predictive performance while also describing the associations and prevalence of known risk factors. The use of this method underlines the importance of combining traditional risk factors with socio-genetic, biological, economic and lifestyle variables, while Anthropological insights reveal the impact of urbanization and socio-cultural norms on health behaviors. Conclusion: The study advocates for a multidisciplinary approach in public health strategies, emphasizing the complex interplay between genetic, environmental, biological and socio-cultural influences on cardiometabolic health. This dual approach aligns with descriptive and predictive model goals. The future research should further integrate biomedical sciences with socio-cultural studies to develop culturally sensitive interventions, aiming to address the growing challenge of CM diseases in urban South Asian contexts.
The evolution of research literature on monk fruit extract and mogroside as sweeteners has yet to be investigated. No study has evaluated this literature from a bibliometric perspective. This bibliometric study analyzed the relevant research literature indexed in Web of Science, to unveil its growth and the most productive authors, institutions, countries, journals, and journal categories. In addition, this study aimed to identify the recurring themes of the literature. On July 2023, the Web of Science Core Collection database was accessed with the following search query: TS = (*mogroside* OR “luo han guo” OR “lo han kuo” OR “monk fruit*” OR “monkfruit*” OR “Siraitia grosvenorii”) AND TS = (sweet*). The search identified publications mentioning these terms in their title, abstract, or keywords. Only articles and reviews were included. No additional filters were placed on publication year, language, etc. Basic publication and citation frequency counts were recorded directly from the database. The complete record of the publications were exported into VOSviewer and CRExplorer, for visualization of recurring terms and identification of commonly cited references, respectively. The search yielded 155 publications. Publication and citation counts have increased steadily since the 2010s. The most productive authors and institutions were mostly based in Asian countries, such as China, Japan, and Singapore. Nearly half of the publications had contributions from China and were published in journals concerning food science technology. The health effects and biosynthesis of mogrosides were the recurring themes among the top 10 most cited publications. Most of the health effects, such as anti-hyperglycemic, anti-hyperlipidemic, and anti-diabetic properties, were demonstrated in animal models with limited evidence from clinical trials. Future studies should focus on testing in humans. Since monk fruit extracts were generally recognized as safe (GRAS) according to the Food and Drug Administration (FDA), the affirmation of these health benefits in humans by future studies should advocate its use in the food industry and the society to generally improve the public health.
Local government organizations experience various obstacles and limitations in implementing the main objective of the decentralization policy, namely administrative decentralization. This goal is essentially the leader of local government organizations carrying out a mission to provide excellent service to the community. Literature studies from various research results from public administration experts reveal that government collaboration is a modern government strategy today to answer and at the same time become a solution to various problems of administering government, especially for local governments. This paper was prepared using the “literature review” method which focuses on revealing how the leadership of regional heads successfully manages government collaboration and how the strategies and leadership roles of public sector organizations in local government manage government collaboration that have an impact on improving service performance to the community. The results of the study recommend that local government leadership requires a transformative leadership strategy, internal and external multi-stakeholder program innovation strategies to carry out positive change agendas. In addition, more specifically, the leaders of government organizations can apply the strategy of “knowledge sharing, designing innovation solutions, Forging consequent change”, and leadership roles as integrators, facilitators, participatory and adaptive.
Political institutions and public administration - Asia (Asian studies only)
Technological advances force every government to digitize its activities, especially in the aspect of public services. Public service is a matter that describes the government of a region. Population documents that must be owned by every community need to be properly provided by the local government. The Sidoarjo Regency Government strengthens population service by using a digital portal named Plavon. The Department of Population and Civil Registration of Sidoarjo Regency continues to innovate and develop the portal properly and is able to provide services. However, the adaptation process sometimes does not work properly due to a lack of understanding and outreach to the community about new service models. The research method used is descriptive qualitative, with data collection techniques carried out by observation, interviews, and documentation. Facilities and infrastructure can be used properly in providing services through the Plavon portal. Service timeliness can also work well. Ease of access runs satisfactorily and is easily understood by users.
Political institutions and public administration - Asia (Asian studies only)
We propose analytical approximations for the sensitivities (Greeks) of the Asian options in the Black-Scholes model, following from a small maturity/volatility approximation for the option prices which has the exact short maturity limit, obtained using large deviations theory. Numerical tests demonstrate good agreement of the proposed approximation with alternative numerical simulation results for cases of practical interest. We also study the qualitative properties of Asian Greeks, including new results for Rho, the sensitivity with respect to changes in the risk-free rate, and Psi, the sensitivity with respect to the dividend yield. In particular we show that the Rho of a fixed-strike Asian option and the Psi of a floating-strike Asian option can change sign.
Language models have been foundations in various scenarios of NLP applications, but it has not been well applied in language variety studies, even for the most popular language like English. This paper represents one of the few initial efforts to utilize the NLP technology in the paradigm of World Englishes, specifically in creating a multi-variety corpus for studying Asian Englishes. We present an overview of the CCAE -- Corpus of Chinese-based Asian English, a suite of corpora comprising six Chinese-based Asian English varieties. It is based on 340 million tokens in 448 thousand web documents from six regions. The ontology of data would make the corpus a helpful resource with enormous research potential for Asian Englishes (especially for Chinese Englishes for which there has not been a publicly accessible corpus yet so far) and an ideal source for variety-specific language modeling and downstream tasks, thus setting the stage for NLP-based World Englishes studies. And preliminary experiments on this corpus reveal the practical value of CCAE. Finally, we make CCAE available at \href{https://huggingface.co/datasets/CCAE/CCAE-Corpus}{this https URL}.
B. Peteet, J. Belliard, J. Abdul‐Mutakabbir
et al.
Public health officials have raised awareness about the disproportionate impact of coronavirus disease (COVID-19) on minoritized populations including Black, Hispanic/Latinx (hereafter Latinx), Asian and Native Americans in testing, infection, hospitalization, and death [1]. The higher infection rate and poorer outcomes in these populations are likely associated with social determinants of health such as living in areas with high rates of COVID-19, crowded living conditions, overrepresentation in high-risk occupations (e.g., essential workers), treatment access disparities, lower health knowledge, and underlying health conditions [2]. In recent months, the federal Food and Drug Administration (FDA) approved three preventative vaccines; yet reports indicated that large portions of U.S. residents did not plan to take the drugs [3]. Vaccine hesitancy is the deferral or refusal of accessible vaccines and varies based on demographic factors such as race/ethnicity, religion, and socioeconomic status [4]. In November of 2020, only 42% of Blacks, compared to 63% of Latinx, 61% of Whites, and 83% of Asian Americans, said they would be willing to take a COVID-19 vaccination if it were available today [5]. Beyond preexisting anti-vaccination attitudes (e.g., Anti/Vax), current mistrust in minoritized communities is primarily driven by historical injustices (e.g., Tuskegee Syphilis Study, eugenics sterilization movement), distrust of the political administration in power at the start of the pandemic, fears about the potential long-term side effects, and the erosion of trust with the healthcare community [6]. As healthcare professionals and public leaders scramble to address vaccine hesitancy, prior research suggests that most likely few are doing so utilizing evidence-based intervention approaches or evaluations, which can backfire [7]. Others are not evaluating or
ABSTRACT The study of how governments deal with the Coronavirus disease-2020 (COVID-19) crisis is becoming a major research stream worldwide. This article contends that the Crisismanship process or system in countries dealing with and controlling this deadly phenomenon should be studied more seriously and more systematically using the novel concept or theory of “surprise management” and “sound governance”. The COVID-19 Crisismanship is offered as a theoretical and conceptual model that refers to a “systematic and dynamic process of the interplay of the three pillars of crisis governance, crisis public administration, and crisis operational activities at the time of a crisis, both vertically and horizontally, with potential overlaps“ as applied to the fight against COVID-19 in Iran. 1 The tireless proactive as well as reactive efforts of Iranian medical scientists and pharmaceutical institutions have resulted in the production of several effective Vaccines as well as treatment drugs in the fight against the Coronavirus. These treatment drugs and vaccines will be used for not only Iran’s population but also supplied to many other countries in the region, Latin America, Asia, and Africa. Nevertheless, the article makes no claim of an Iran’s perfect or complete success in controlling or defeating COVID-19, as no one can. Iran has lost over 50,000 lives with over one million infected. Yet, the article does suggest that lessons learned from the Iranian government’s responses to the COVID-19 may help other countries in a fight against similar pandemic crises in the future.
The greatest achievement of ASEAN’s intra-regional economic cooperation since its inception in 1976 is the realization of the ASEAN Free Trade Area (AFTA), which started with tariff cuts in 1993. AFTA was completed in January 2018 with the elimination of intra-regional tariffs. The AFTA itself is an FTA of an unusually high standard internationally, with the level of liberalization exceeding even that of the TPP 11. However, when examined from the aspect of utilization, in the case of Thailand’s exports to ASEAN, more than 30% do not use AFTA for one reason or another. This indicates that there are points of improvement in the system of the AFTA and in the customs procedures that are indispensable in using the AFTA. Furthermore, some member countries have introduced non-tariff barriers to protect their domestic industries while eliminating tariffs, which is contrary to the principles of AFTA. ASEAN has been expanding the scope of its economic cooperation since 2008 with the aim of establishing the ASEAN Economic Community (AEC), but even so, what the industrial world is seeking in the “post-AFTA” periods are trade-related measures such as the “facilitation of customs procedures” and the “elimination of non-tariff barriers.” Nowadays, when mega FTAs such as RCEP and TPP11 is being constructed one after another, ASEAN needs to transform itself into the most advanced regional cooperation organization in terms of liberalization level, scope, and rules if it is to maintain its centripetal force for direct investment.
Political institutions and public administration - Asia (Asian studies only), Social sciences and state - Asia (Asian studies only)
This article explores a facet of the Chinese propaganda apparatus that has yet to receive sufficient academic attention: the murky ecosystem of “semi-official” party-state presences on Chinese social media. With a particular focus on WeChat public accounts, this investigation responds to two critical research questions: first, what differentiates official party-state social media presences from semi-official presences, and second, what unique role do semi-official WeChat accounts play in the contemporary Chinese propaganda apparatus? This article samples content published by five dyads of official and semi-official WeChat public accounts during the first fifteen days of June 2019. The results of this comparative, case-study-based discourse analysis support two conclusions. First, semi-official WeChat accounts posture as independent from the party-state in order to attract large followings and gain credibility. Second, semi-official WeChat public accounts operate as “astroturfed influencers,” enabling the Chinese propaganda apparatus to covertly manipulate online discourse with extraordinary efficiency.
Political institutions and public administration - Asia (Asian studies only), Social sciences and state - Asia (Asian studies only)
A Sidon space is a subspace of an extension field over a base field in which the product of any two elements can be factored uniquely, up to constants. This paper proposes a new public-key cryptosystem of the multivariate type which is based on Sidon spaces, and has the potential to remain secure even if quantum supremacy is attained. This system, whose security relies on the hardness of the well-known MinRank problem, is shown to be resilient to several straightforward algebraic attacks. In particular, it is proved that the two popular attacks on the MinRank problem, the kernel attack, and the minor attack, succeed only with exponentially small probability. The system is implemented in software, and its hardness is demonstrated experimentally.
Vinodkumar Prabhakaran, Marek Rei, Ekaterina Shutova
Metaphors are widely used in political rhetoric as an effective framing device. While the efficacy of specific metaphors such as the war metaphor in political discourse has been documented before, those studies often rely on small number of hand-coded instances of metaphor use. Larger-scale topic-agnostic studies are required to establish the general persuasiveness of metaphors as a device, and to shed light on the broader patterns that guide their persuasiveness. In this paper, we present a large-scale data-driven study of metaphors used in political discourse. We conduct this study on a publicly available dataset of over 85K posts made by 412 US politicians in their Facebook public pages, up until Feb 2017. Our contributions are threefold: we show evidence that metaphor use correlates with ideological leanings in complex ways that depend on concurrent political events such as winning or losing elections; we show that posts with metaphors elicit more engagement from their audience overall even after controlling for various socio-political factors such as gender and political party affiliation; and finally, we demonstrate that metaphoricity is indeed the reason for increased engagement of posts, through a fine-grained linguistic analysis of metaphorical vs. literal usages of 513 words across 70K posts.