The study analyzes millions of German-language online articles and tweets from 2019–2022 to uncover political biases using automated text analysis. It finds that international events such as the COVID‑19 pandemic and the Ukraine war create thematic convergence between German and Swiss media, while domestic policy differences drive divergence in locally focused topics. Newspapers maintain more stable political content, whereas Twitter shows rapid, event‑driven spikes, illustrating how media platforms differ in intensity and timing.
By Yara D\"oring, Felix Bie{\ss}mann
arXiv:2608. 12422v1 Announce Type: new Abstract: Two free satellite signals carry real information about glacial-lake outburst risk in the Nepal Himalaya: radar interferometry sees a moraine dam slowly sagging, and satellite weather marks the weeks when a primed lake is under stress.
By Matthew Kahn, Milan Arjel, Nirmala Adhikari, Mingmar Sherpa, James Pope
arXiv:2609.35821v2 Announce Type: replace
Abstract: Disaster social sensing converts public social-media posts into evidence for situational awareness and humanitarian response, but plausible LLM-gen...
By Xiaoshan Zhou, Zaifu Zhan
BharatGather is a curated, multi-source dataset designed for binary misinformation classification in Indian public events such as religious festivals, political rallies, and cultural gatherings. The corpus contains 14,646 records assembled through systematic web scraping of fact‑checking platforms, multimedia transcript extraction, and LLM‑mediated synthetic augmentation to capture narrative diversity. It serves as a culturally informed benchmark to evaluate and develop fake‑news detection systems tailored to the socio‑cultural nuances of India’s mass‑gathering context.
By Parth Bramhecha, Smit Deshmukh, Sairaj Bodhale, Adwait Borate, Raviraj Joshi
The paper investigates affective framing in Bengali digital journalism by analyzing 300,000 news headlines with zero‑shot inference using Gemma 3 4B to estimate dominant emotions and overall affective tone. Results reveal frequent negative emotions—especially anger, sadness, disappointment, and fear—across the corpus, and a pilot validation on 200 headlines indicates the model’s estimates are useful yet not definitive benchmarks. The authors suggest a bias‑sensitive news interface that visualizes emotional cues to help readers detect affective framing patterns in daily news.
By Mohd Ruhul Ameen, Akif Islam, Ayesha Siddiqua, Abu Saleh Musa Miah, Jungpil Shin
arXiv:2607. 02734v1 Announce Type: cross Abstract: Rapid growth in social media has transformed global communication by enabling fast information exchange, but it has also accelerated the spread of misinformation.
By Md. Maruf Bangabashi, Tahmid Hasan, Golam Mahmud, Md. Mostafijur Rahman, Md. Toufiqur Rahman, Jahanur Biswas
arXiv:2610.15403v1 Announce Type: new
Abstract: Crowdsourced disaster imagery provides timely, ground-level observations when conventional disaster mapping is delayed or incomplete, yet its geographi...
By Hao Li, Wenping Yin, Fabian Deuser, Jia Jia, Ziqi Liu, Levente Juh\'asz, Fan Zhang, Filip Biljecki
arXiv:2405. 17838v3 Announce Type: replace-cross Abstract: Socio-linguistic indicators of affectively-relevant phenomena, such as emotion or sentiment, are often extracted from text to better understand features of human-computer interactions, including on social media.
By Keith Burghardt, Daniel M. T. Fessler, Chyna Tang, Anne Pisor, Kristina Lerman
arXiv:2509.22030v2 Announce Type: replace
Abstract: This paper examines how outliers, often dismissed as noise in topic modeling, can act as weak signals of emerging topics in dynamic news corpora. U...
By Evangelia Zve, Benjamin Icard, Alice Breton, Lila Sainero, Gauvain Bourgne, Jean-Gabriel Ganascia
arXiv:2607. 24856v1 Announce Type: cross Abstract: Social media imagery (SMI) provides timely and fine-grained ground perspectives that are valuable for situational awareness and emergency response.
By Wenping Yin, Ziqi Liu, Naixia Mou, Weijia Li, Danfeng Hong, Hao Li
arXiv:2609.00712v1 Announce Type: new
Abstract: Landslides are widespread geological hazards, yet their automated detection and mapping in remote sensing imagery remain challenging because of their i...
By Yuanchao Su, Lianru Gao, Mengying Jiang, Jiangyi Chen, Jiaxin Cheng, Yicong Zhou
arXiv:2607.04962v2 Announce Type: replace
Abstract: Conspiracy theories commonly attribute important events to the actions of powerful and secretive actors. While computational research has largely f...
By Helena Mihaljevi\'c, Jolanda Beer, Mareike Lisker, Katharina Soemer