相关论文: Sentiment Analysis of Twitter Posts on Global Conf…

The growing incidents of counterfeiting and associated economic and health consequences necessitate the development of active surveillance systems capable of producing timely and reliable information for all stake holders in the…

With the expansion of mobile communications infrastructure, social media usage in the Global South is surging. Compared to the Global North, populations of the Global South have had less prior experience with social media from stationary…

Analysis of information retrieved from microblogging services such as Twitter can provide valuable insight into public sentiment in a geographic region. This insight can be enriched by visualising information in its geographic context. Two…

Social media provides many opportunities to monitor and evaluate political phenomena such as referendums and elections. In this study, we propose a set of approaches to analyze long-running political events on social media with a real-world…

Online firestorms on Twitter are seemingly arbitrarily occurring outrages towards people, companies, media campaigns and politicians. Moral outrages can create an excessive collective aggressiveness against one single argument, one single…

In recent years, sentiment analysis and emotion classification are two of the most abundantly used techniques in the field of Natural Language Processing (NLP). Although sentiment analysis and emotion classification are used commonly in…

With the popularity of social networks, and e-commerce websites, sentiment analysis has become a more active area of research in the past few years. On a high level, sentiment analysis tries to understand the public opinion about a specific…

In recent years, we have been faced with a series of natural disasters causing a tremendous amount of financial, environmental, and human losses. The unpredictable nature of natural disasters' behavior makes it hard to have a comprehensive…

The conflict in Ukraine has been not only characterised by military engagement but also by a significant information war, with social media platforms like X, formerly known as Twitter playing an important role in shaping public perception.…

Sentiment in social media is increasingly considered as an important resource for customer segmentation, market understanding, and tackling other socio-economic issues. However, sentiment in social media is difficult to measure since…

Social media is commonly used by the public during election campaigns to express their opinions regarding different issues. Among various social media channels, Twitter provides an efficient platform for researchers and politicians to…

Agonism plays a vital role in democratic dialogue by fostering diverse perspectives and robust discussions. Within the realm of online conflict there is another type: hateful antagonism, which undermines constructive dialogue. Detecting…

Twitter sentiment analysis, which often focuses on predicting the polarity of tweets, has attracted increasing attention over the last years, in particular with the rise of deep learning (DL). In this paper, we propose a new task:…

Domain adaptation is important in sentiment analysis as sentiment-indicating words vary between domains. Recently, multi-domain adaptation has become more pervasive, but existing approaches train on all available source domains including…

On February 24, 2022, Russia invaded Ukraine. In the days that followed, reports kept flooding in from layman to news anchors of a conflict quickly escalating into war. Russia faced immediate backlash and condemnation from the world at…

Climate change is one of the most pressing challenges of the 21st century, sparking widespread discourse across social media platforms. Activists, policymakers, and researchers seek to understand public sentiment and narratives while access…

In this paper , we tackle Sentiment Analysis conditioned on a Topic in Twitter data using Deep Learning . We propose a 2-tier approach : In the first phase we create our own Word Embeddings and see that they do perform better than…

This paper studies users' perception regarding a controversial product, namely self-driving (autonomous) cars. To find people's opinion regarding this new technology, we used an annotated Twitter dataset, and extracted the topics in…

Online social media such as Twitter are widely used for mining public opinions and sentiments on various issues and topics. The sheer volume of the data generated and the eager adoption by the online-savvy public are helping to raise the…

This paper proposes a novel lexicon-based unsupervised sentimental analysis method to measure the $``\textit{hope}"$ and $``\textit{fear}"$ for the 2022 Ukrainian-Russian Conflict. $\textit{Reddit.com}$ is utilised as the main source of…