Political stance detection in low-resource and culturally complex settings poses a critical challenge for large language models (LLMs). In the Thai political landscape - marked by indirect language, polarized figures, and entangled sentiment and stance - LLMs often display systematic biases such as sentiment leakage and favoritism toward entities. These biases undermine fairness and reliability. We present ThaiFACTUAL, a lightweight, model-agnostic calibration framework that mitigates political bias without requiring fine-tuning. ThaiFACTUAL uses counterfactual data augmentation and rationale-based supervision to disentangle sentiment from stance and reduce bias. We also release the first high-quality Thai political stance dataset, annotated with stance, sentiment, rationales, and bias markers across diverse entities and events. Experimental results show that ThaiFACTUAL significantly reduces spurious correlations, enhances zero-shot generalization, and improves fairness across multiple LLMs. This work highlights the importance of culturally grounded debiasing techniques for underrepresented languages.

In today's digital age, images have emerged as powerful tools for politicians to engage with their voters on social media platforms. Visual content possesses a unique emotional appeal that often leads to increased user engagement. However, research on visual communication remains relatively limited, particularly in the Global South. This study aims to bridge this gap by employing a combination of computational methods and qualitative approach to investigate the visual communication strategies employed in a dataset of 11,263 Instagram posts by 19 Brazilian presidential candidates in 2018 and 2022 national elections. Through two studies, we observed consistent patterns across these candidates on their use of visual political communication. Notably, we identify a prevalence of celebratory and positively toned images. They also exhibit a strong sense of personalization, portraying candidates connected with their voters on a more emotional level. We note a substantial presence of screenshots from news websites and other social media platforms. Furthermore, text-edited images with portrayals emerge as a prominent feature. In light of these results, we engage in a discussion regarding the implications for the broader field of visual political communication. This article serves as a testament to the pivotal role that Instagram has played in shaping the narrative of two fiercely polarized Brazilian elections, casting a revealing light on the ever-evolving dynamics of visual political communication in the digital age. Finally, we propose avenues for future research in the realm of visual political communication. Introduction In the ever-evolving arena of election campaigns, candidates rely heavily on the media as their megaphone to amplify their messages to the masses. Over the years, the landscape of political communication has undergone a profound transformation. This transformation has been driven by the rise of online social media platforms, which have emerged as indispensable tools for candidates in their quest to gauge public sentiment and rally support from the electorate (Boulianne & Olof Larsson, 2023; Farkas & Bene, 2021). The significance of this transformation has been further accentuated by the global ascent of populist leaders, spanning diverse nations, who have wholeheartedly embraced social media as their primary mode of communication (Bernardi & Costa, 2020; Novoselova, 2020).

Sentiment analysis using big data from YouTube videos metadata can be conducted to analyze public opinions on various political figures who represent political parties. This is possible because YouTube has become one of the platforms for people to express themselves, including their opinions on various political figures. The resulting sentiment analysis can be useful for political executives to gain an understanding of public sentiment and develop appropriate and effective political strategies. This study aimed to build a sentiment analysis system leveraging YouTube videos metadata. The sentiment analysis system was built using Apache Kafka, Apache PySpark, and Hadoop for big data handling; TensorFlow for deep learning handling; and FastAPI for deployment on the server. The YouTube videos metadata used in this study is the video description. The sentiment analysis model was built using LSTM algorithm and produces two types of sentiments: positive and negative sentiments. The sentiment analysis results are then visualized in the form a simple web-based dashboard.

AI bot ChatGPT has made waves around the world with its eerie ability to generate human-like text - but how well can it impersonate famous people? Below, we've generated tweets using the chatbot in the style of famous tweeters from Elon Musk to Joe Biden, and put them next to recent examples - but can you tell them apart? ChatGPT's ability to generate text'in the style of' real people'is already controversial - singer Nick Cave described it as a'grotesque mockery of what it means to be human' after a fan generated lyrics in his style. For our quiz, we used simple prompts such as, 'Write a tweet in the style of Joe Biden', but ChatGPT's natural-language interface means that users can'force' famous people to say just about anything they want in their own style. Scroll to the bottom to see which tweets are real and which are ChatGPT fakes.

I am spending my last weeks on thinking about climate actions, sustainability and economical aspects of these. I listened to a lot of podcasts about these topics, and I have tens of notes from these podcasts. I decided to express my ideas about this topic. But no, it is not my turn to spread the ideas. Only thing I wrote for this article is headline and a couple of keywords.

Facing growing pressure to fight disinformation ahead of the 2020 presidential election, Twitter said it would label or remove tweets sharing doctored videos and photos, sometimes referred to as deepfakes, that seek to mislead users. Under the new policy, Twitter users cannot "deceptively" share altered videos and photos that are "likely to cause harm," the company said Tuesday. "We've seen people try to distort conversations with altered media or fabricated media, not just on Twitter, but across the internet," Del Harvey, Twitter's vice president of trust and safety, said. "We want to make sure we can address any instance where media has been altered or fabricated and shared on Twitter." Video clips deceptively altered to discredit or embarrass political figures, such as those targeting House Speaker Nancy Pelosi and Democratic presidential candidate Joe Biden, would be labeled, the company said Tuesday.

Deepfakes are video manipulations that can make people say seemingly strange things. Barack Obama and Nicolas Cage have been featured in these videos. A video of President Donald Trump singing "America the Beautiful" received over 50,000 views on Instagram when it was posted just before the July 4th holiday. Did the president really record a video of himself singing and post it to social media? But with the growing prevalence of altered videos and intentional mischief, the question "Is it real?" is one we will need to ask with more regularity.

Sharing a name with a famous person can prompt endless jokes and comments -- but in these particularly politically-charged times, having the same name as a political figure can be especially tiresome. That's something a young man from Kentucky named Brett Kavanagh has learned only too well in recent weeks: On Friday, Brett, 27, complained about the recent woes of having his name, prompting others with famous names to commiserate. Women named Siri and Alexa, and men named Michael Jackson and Bruce Lee, all tweeted about how hard it is to have a well-known name. His tweet inspired others to chime in, including this person who pointed to a Scottish man named Steve Bannon -- who is not the same as Breitbart's Steve Bannon A man named Bruce Y. Lee knows the struggle This Brett, who works in customer service and lives in Louisville, spells his last name differently from new Supreme Court Justice Brett Kavanaugh, but it seems their nearly-identical names has caused him some trouble. Tough times: Brett (pictured) doesn't spell his name the same way as the judge, either'This is a terrible time to be named Brett Kavanagh,' he tweeted.