相关论文: Linking Twitter Events With Stock Market Jitters

Twitter is recognized as a crucial platform for the dissemination and gathering of Cyber Threat Intelligence (CTI). Its capability to provide real-time, actionable intelligence makes it an indispensable tool for detecting security events,…

Identifying user stance related to a political event has several applications, like determination of individual stance, shaping of public opinion, identifying popularity of government measures and many others. The huge volume of political…

Social media such as tweets are emerging as platforms contributing to situational awareness during disasters. Information shared on Twitter by both affected population (e.g., requesting assistance, warning) and those outside the impact zone…

Cities have been a thriving place for citizens over the centuries due to their complex infrastructure. The emergence of the Cyber-Physical-Social Systems (CPSS) and context-aware technologies boost a growing interest in analysing,…

Study of the forecasting models using large scale microblog discussions and the search behavior data can provide a good insight for better understanding the market movements. In this work we collected a dataset of 2 million tweets and…

In the modern economic landscape, integrating financial services with Financial Technology (FinTech) has become essential, particularly in stock trend analysis. This study addresses the gap in comprehending financial dynamics across diverse…

In this work, we tackle the problem of predicting entity popularity on Twitter based on the news cycle. We apply a supervised learn- ing approach and extract four types of features: (i) signal, (ii) textual, (iii) sentiment and (iv)…

The ability to track and monitor relevant and important news in real-time is of crucial interest in multiple industrial sectors. In this work, we focus on the set of cryptocurrency news, which recently became of emerging interest to the…

Event detection has been one of the most important research topics in social media analysis. Most of the traditional approaches detect events based on fixed temporal and spatial resolutions, while in reality events of different scales…

With the rise in popularity of public social media and micro-blogging services, most notably Twitter, the people have found a venue to hear and be heard by their peers without an intermediary. As a consequence, and aided by the public…

The gargantuan plethora of opinions, facts and tweets on financial business offers the opportunity to test and analyze the influence of such text sources on future directions of stocks. It also creates though the necessity to distill via…

Financial market forecasting is one of the most attractive practical applications of sentiment analysis. In this paper, we investigate the potential of using sentiment \emph{attitudes} (positive vs negative) and also sentiment…

The Web is a vast virtual space where people can share their opinions, impacting all aspects of life and having implications for marketing and communication. The most up-to-date and comprehensive information can be found on social media…

Nowadays, social medias such as Twitter, Memetracker and Blogs have become powerful tools to propagate information. They facilitate quick dissemination sequence of information such as news article, blog posts, user's interests and thoughts…

The intersection of social media, low-cost trading platforms, and naive investors has created an ideal situation for information-based market manipulations, especially pump&dumps. Manipulators accumulate small-cap stocks, disseminate false…

We propose how to quantify high-frequency market sentiment using high-frequency news from NASDAQ news platform and support vector machine classifiers. News arrive at markets randomly and the resulting news sentiment behaves like a…

Twitter is perhaps the social media more amenable for research. It requires only a few steps to obtain information, and there are plenty of libraries that can help in this regard. Nonetheless, knowing whether a particular event is expressed…

Streams of user-generated content in social media exhibit patterns of collective attention across diverse topics, with temporal structures determined both by exogenous factors and endogenous factors. Teasing apart different topics and…

Cryptocurrencies have emerged as a novel financial asset garnering significant attention in recent years. A defining characteristic of these digital currencies is their pronounced short-term market volatility, primarily influenced by…

This paper is devoted to problem of detecting critical events at finiacial markets using methods of multifractal analysis. Namely, the local regularity of time-series is studied. As a result, one can find out a special behavior or signal of…