Detecting political bias in news media is a complex task that requires interpreting subtle linguistic and contextual cues. Although recent advances in Natural Language Processing (NLP) have enabled automatic bias classification, the extent to which large language models (LLMs) align with human judgment still remains relatively underexplored and not yet well understood. This study aims to present a comparative framework for evaluating the detection of political bias across human annotations and multiple LLMs, including GPT, BERT, RoBERTa, and FLAN. We construct a manually annotated dataset of news articles and assess annotation consistency, bias polarity, and inter-model agreement to quantify divergence between human and model perceptions of bias. Experimental results show that among traditional transformer-based models, RoBERTa achieves the highest alignment with human labels, whereas generative models such as GPT demonstrate the strongest overall agreement with human annotations in a zero-shot setting. Among all transformer-based baselines, our fine-tuned RoBERTa model acquired the highest accuracy and the strongest alignment with human-annotated labels. Our findings highlight systematic differences in how humans and LLMs perceive political slant, underscoring the need for hybrid evaluation frameworks that combine human interpretability with model scalability in automated media bias detection.

Next week, five teens from Palestine will head to Panama to compete in one of the world's largest youth robotics competitions. To win--and then teach STEM to their peers displaced by the Israel-Hamas war. For the entirety of the past year, as the teenage roboticists of Team Palestine have been working on their latest project, their homeland has been engulfed in Israel's war with Hamas . Earlier this month, that all changed. With a fragile ceasefire in place, Israeli forces began to pull back from parts of Gaza, and the teens put the final touches on the project they hope will bring them victory: a robot that can maneuver through a series of simulated challenges based on the effects of climate change.

Can Israel survive economic isolation? Why have Spain and Italy sent ships to assist the Gaza Sumud flotilla? Italy and Spain have decided this week to dispatch naval vessels to assist the Global Sumud Flotilla on its way to break Israel's siege of Gaza. The unprecedented move to support a flotilla headed towards the Palestinian enclave comes after repeated attacks against the Sumud Flotilla, including a drone attack early on Wednesday. Israel is widely believed to be behind the attacks.

Is recognising Palestine a way to'save face' for Western leaders? This is the moment a drone launched by Yemen's Houthis exploded in the Israeli city of Eilat. Footage shows it over the southern port city before bursting into flames in a residential neighbourhood, injuring at least 22 people, after Israeli military failed to intercept it. Finland's president hails rise of global south at UNGA Estonia calls Russian jets violating its airspace a'hostile act'

Is recognising Palestine a way to'save face' for Western leaders? A Spanish naval vessel will join the Global Sumud Flotilla for Gaza to provide assistance and, if necessary, conduct rescues, Spanish Prime Minister Pedro Sanchez has said. Italy earlier announced it was dispatching a frigate after a night of drone attacks on the humanitarian flotilla opposed by the Israeli government. Finland's president hails rise of global south at UNGA Estonia calls Russian jets violating its airspace a'hostile act'

Is recognising Palestine a way to'save face' for Western leaders? Activists say Israeli drones carried out several attacks on the Gaza-bound Global Sumud Flotilla, dropping explosive devices near several boats but causing no injuries. Chile's president draws parallel between Gaza and Holocaust at UNGA

Is recognising Palestine a way to'save face' for Western leaders? Organisers of the Global Sumud Flotilla, a Gaza-bound flotilla with pro-Palestinian activists on board carrying aid, reported hearing explosions and seeing multiple drone attacks from their boats situated off Greece from late Tuesday to the early hours of Wednesday. "Multiple drones, unidentified objects dropped, communications jammed and explosions heard from a number of boats," the Global Sumud Flotilla said in a statement, without adding whether there were any casualties. "We are witnessing these psychological operations firsthand, right now, but we will not be intimidated." Suited in a life jacket, Brazilian organiser Tiago Avila updated on his Instagram at midnight on Wednesday that a total of 10 attacks targeted multiple boats with sound bombs and explosive flares.

The Israeli-Palestinian conflict started on 7 October 2023, have resulted thus far to over 48,000 people killed including more than 17,000 children with a majority from Gaza, more than 30,000 people injured, over 10,000 missing, and over 1 million people displaced, fleeing conflict zones. The infrastructure damage includes the 87\% of housing units, 80\% of public buildings and 60\% of cropland 17 out of 36 hospitals, 68\% of road networks and 87\% of school buildings damaged. This conflict has as well launched an online discussion across various social media platforms. Telegram was no exception due to its encrypted communication and highly involved audience. The current study will cover an analysis of the related discussion in relation to different participants of the conflict and sentiment represented in those discussion. To this end, we prepared a dataset of 125K messages shared on channels in Telegram spanning from 23 October 2025 until today. Additionally, we apply the same analysis in two publicly available datasets from Twitter containing 2001 tweets and from Reddit containing 2M opinions. We apply a volume analysis across the three datasets, entity extraction and then proceed to BERT topic analysis in order to extract common themes or topics. Next, we apply sentiment analysis to analyze the emotional tone of the discussions. Our findings hint at polarized narratives as the hallmark of how political factions and outsiders mold public opinion. We also analyze the sentiment-topic prevalence relationship, detailing the trends that may show manipulation and attempts of propaganda by the involved parties. This will give a better understanding of the online discourse on the Israel-Palestine conflict and contribute to the knowledge on the dynamics of social media communication during geopolitical crises.

This study uses the Palestinian Oral History Archive (POHA) to investigate how Palestinian refugee groups in Lebanon sustain a cohesive collective memory of the Nakba through shared narratives. Grounded in Halbwachs' theory of group memory, we employ statistical analysis of pairwise similarity of narratives, focusing on the influence of shared gender and location. We use textual representation and semantic embeddings of narratives to represent the interviews themselves. Our analysis demonstrates that shared origin is a powerful determinant of narrative similarity across thematic keywords, landmarks, and significant figures, as well as in semantic embeddings of the narratives. Meanwhile, shared residence fosters cohesion, with its impact significantly amplified when paired with shared origin. Additionally, women's narratives exhibit heightened thematic cohesion, particularly in recounting experiences of the British occupation, underscoring the gendered dimensions of memory formation. This research deepens the understanding of collective memory in diasporic settings, emphasizing the critical role of oral histories in safeguarding Palestinian identity and resisting erasure.

Large language models (LLMs) have gained significant attention over the past few years, particularly following the emergence of ChatGPT, both from researchers Movva et al. [2024] and in terms of their adoption in the private sector. This hype has revolutionized how we use AI in different fields and helped redefine how various domains utilize AI, such as in medicine Alghamdi and Mostafa [2024], Yuan et al. [2024], finance Xie et al. [2024], Malaysha et al. [2024], and even agriculture Gupta et al. [2024]. These advancements demonstrate the profound potential of AI to transform industries, driving innovation and efficiency in ways previously unimaginable. However, one domain that still has room for growth and the potential to bring about significant change is the legal domain Martin et al. [2024], Maree et al. [2024]. Although sectors such as healthcare and finance have rapidly adopted AI to address their unique challenges, the legal industry has been relatively slow to embrace these technologies Legg and Bell [2020]. The complex nature of legal language, coupled with jurisdictional variations and the high stakes involved, and the lack of AI regulations de Almeida et al. [2021], Nadjia [2024], has presented significant obstacles to developing effective AI-powered legal