Related papers: Sentiment Analysis on Social Media Content
All groups of people felt the impact of the COVID-19 pandemic. This situation triggers anxiety, which is bad for everyone. The government's role is very influential in solving these problems with its work program. It also has many pros and…
This study uses sentiment analysis and the Moral Foundations Theory (MFT) to characterise news content in social media and examine its association with user engagement. We employ Natural Language Processing to quantify the moral and…
Tweet sentiment extraction extracts the most significant portion of the sentence, determining whether the sentiment is positive or negative. This research aims to identify the part of tweet sentences that strikes any emotion. To reach this…
Nowadays, with the rise of Internet access and mobile devices around the globe, more people are using social networks for collaboration and receiving real-time information. Twitter, the microblogging that is becoming a critical source of…
This study explores the intersection of fashion trends and social media sentiment through computational analysis of Twitter data using the T4SA (Twitter for Sentiment Analysis) dataset. By applying natural language processing and machine…
In this paper, we investigate the issue of detecting the real-life influence of people based on their Twitter account. We propose an overview of common Twitter features used to characterize such accounts and their activity, and show that…
In this paper we present a method to identify tweets that a user may find interesting enough to retweet. The method is based on a global, but personalized classifier, which is trained on data from several users, represented in terms of…
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…
This article aims to exploit social exchanges on scientific literature, specifically tweets, to analyse social media users' sentiments towards publications within a research field. First, we employ the SentiStrength tool, extended with…
Micro-blogging sources such as the Twitter social network provide valuable real-time data for market prediction models. Investors' opinions in this network follow the fluctuations of the stock markets and often include educated speculations…
Social Media has seen a tremendous growth in the last decade and is continuing to grow at a rapid pace. With such adoption, it is increasingly becoming a rich source of data for opinion mining and sentiment analysis. The detection and…
Being able to predict stock prices might be the unspoken wish of stock investors. Although stock prices are complicated to predict, there are many theories about what affects their movements, including interest rates, news and social media.…
Linguistics has been instrumental in developing a deeper understanding of human nature. Words are indispensable to bequeath the thoughts, emotions, and purpose of any human interaction, and critically analyzing these words can elucidate the…
In todays competitive business world, being aware of customer needs and market-oriented production is a key success factor for industries. To this aim, the use of efficient analytic algorithms ensures a better understanding of customer…
This workshop paper reports on an ongoing mixed-methods study on the two arguably most popular social network sites, Facebook and Twitter, for the same users. The overarching goal of the study is to shed light into the nuances of social…
We introduce a stochastic model which describes diffusions of tweets on the Twitter network. By dividing the followers into generations, we describe the dynamics of the tweet diffusion as a random multiplicative process. We confirm our…
Hate speech detection on Twitter is critical for applications like controversial event extraction, building AI chatterbots, content recommendation, and sentiment analysis. We define this task as being able to classify a tweet as racist,…
The amount of user generated contents from various social medias allows analyst to handle a wide view of conversations on several topics related to their business. Nevertheless keeping up-to-date with this amount of information is not…
In recent years, social media has become ubiquitous and important for social networking and content sharing. And yet, the content that is generated from these websites remains largely untapped. In this paper, we demonstrate how social media…
A vast amount of textual web streams is influenced by events or phenomena emerging in the real world. The social web forms an excellent modern paradigm, where unstructured user generated content is published on a regular basis and in most…