Topic modeling is one of the most powerful techniques in text mining for data mining, latent data discovery, and finding relationships among data and text documents. Researchers have published many articles in the field of topic modeling and applied in various fields such as software engineering, political science, medical and linguistic science, etc. There are various methods for topic modelling; Latent Dirichlet Allocation (LDA) is one of the most popular in this field. Researchers have proposed various models based on the LDA in topic modeling. According to previous work, this paper will be very useful and valuable for introducing LDA approaches in topic modeling. In this paper, we investigated highly scholarly articles (between 2003 to 2016) related to topic modeling based on LDA to discover the research development, current trends and intellectual structure of topic modeling. In addition, we summarize challenges and introduce famous tools and datasets in topic modeling based on LDA.
This article challenges Fixed Effects (FE) modeling as the ‘default’ for time-series-cross-sectional and panel data. Understanding different within and between effects is crucial when choosing modeling strategies. The downside of Random Effects (RE) modeling—correlated lower-level covariates and higher-level residuals—is omitted-variable bias, solvable with Mundlak's (1978a) formulation. Consequently, RE can provide everything that FE promises and more, as confirmed by Monte-Carlo simulations, which additionally show problems with Plümper and Troeger's FE Vector Decomposition method when data are unbalanced. As well as incorporating time-invariant variables, RE models are readily extendable, with random coefficients, cross-level interactions and complex variance functions. We argue not simply for technical solutions to endogeneity, but for the substantive importance of context/heterogeneity, modeled using RE. The implications extend beyond political science to all multilevel datasets. However, omitted variables could still bias estimated higher-level variable effects; as with any model, care is required in interpretation.
Science studies has shown us why science and technology cannot always solve technical problems in the public domain. In particular, the speed of political decision-making is faster than the speed of scientific consensus formation. A predominant motif over recent years has been the need to extend the domain of technical decision-making beyond the technically qualified élite, so as to enhance political legitimacy. We argue, however, that the `Problem of Legitimacy' has been replaced by the `Problem of Extension' - that is, by a tendency to dissolve the boundary between experts and the public so that there are no longer any grounds for limiting the indefinite extension of technical decision-making rights. We argue that a Third Wave of Science Studies - Studies of Expertise and Experience (SEE) - is needed to solve the Problem of Extension. SEE will include a normative theory of expertise, and will disentangle expertise from political rights in technical decision-making. The theory builds categories of expertise, starting with the key distinction between interactive expertise and contributory expertise. A new categorization of types of science is also needed. We illustrate the potential of the approach by re-examining existing case studies, including Brian Wynne's study of Cumbrian sheep farmers. Sometimes the new theory argues for more public involvement, sometimes for less. An Appendix describes existing contributions to the problem of technical decision-making in the public domain.
Politics today is largely about the art of messaging to influence the public, but the mathematical theory of messaging -- information and communication theory -- can turn this art into a precise analysis, both qualitative and quantitative, that enables us to gain retrospective understandings of past political events and to make forward-looking future predictions.
The article is dedicated to reflections on the activities of the prominent Austrian politician, diplomat, and public figure Walter Schwimmer (1942–2025). The author examines in detail his contributions to the development of European integration, the protection of human rights, and the promotion of intercivilizational dialogue. Special attention is given to analyzing Schwimmer's works, his public speeches, and his book «Dreams of Europe», where he advocates for the idea of a large peaceful European home without dividing borders. The article explores Schwimmer's political career, his tenure as Secretary-General of the Council of Europe (1999–2004), as well as his work as Director of the Coordinating Committee of the World Public Forum “Dialogue of Civilizations”. The author reveals Schwimmer's views on contemporary global challenges, including combating terrorism, the rise of populism, threats to democracy, reforming international institutions, and building strategic cooperation between Europe and Russia.
Krisman Heriamsal, Rivelda Pricilia Heatubun, Heyna Jekaisa
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The water scarcity crisis in Iraq has become a non-traditional security issue that threatens the country's social, political and economic stability. According to international data, water scarcity is predicted to worsen by 2030, affecting more than 700 million people worldwide. Iraq, which depends on the flow of the Tigris and Euphrates rivers, is experiencing a decline in water quality and quantity that is worsening agricultural conditions, increasing social tensions and causing internal migration. This article analyzes the Iraqi government's efforts to address the water crisis through diplomacy by joining the Paris Agreement and the UN Water Convention, as well as organizing the Baghdad International Water Conference. This research uses a descriptive qualitative approach to explore the impact of water scarcity in Iraq and the diplomatic responses undertaken for mitigation. Although formal diplomacy has resulted in international aid and mitigation projects, climate change impacts and domestic governance issues, such as corruption, hamper the effectiveness of such efforts. This article also suggests the need for non-formal diplomacy involving non-state actors to improve the effectiveness of solving the water crisis in Iraq.
The advancement of generative AI, particularly large language models (LLMs), has a significant impact on politics and democracy, offering potential across various domains, including policymaking, political communication, analysis, and governance. This paper surveys the recent and potential applications of LLMs in politics, examining both their promises and the associated challenges. This paper examines the ways in which LLMs are being employed in legislative processes, political communication, and political analysis. Moreover, we investigate the potential of LLMs in diplomatic and national security contexts, economic and social modeling, and legal applications. While LLMs offer opportunities to enhance efficiency, inclusivity, and decision-making in political processes, they also present challenges related to bias, transparency, and accountability. The paper underscores the necessity for responsible development, ethical considerations, and governance frameworks to ensure that the integration of LLMs into politics aligns with democratic values and promotes a more just and equitable society.
Dominik Stammbach, Philine Widmer, Eunjung Cho
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Large language models such as ChatGPT exhibit striking political biases. If users query them about political information, they often take a normative stance. To overcome this, we align LLMs with diverse political viewpoints from 100,000 comments written by candidates running for national parliament in Switzerland. Models aligned with this data can generate more accurate political viewpoints from Swiss parties, compared to commercial models such as ChatGPT. We also propose a procedure to generate balanced overviews summarizing multiple viewpoints using such models. The replication package contains all code and data.