We also describe the process of preparing the dataset and present its analysis, including entity and annotator bias analysis, and some insights into possible challenges of the task of entity-level analysis of the news.doi:10.1016/j.procs.2021.09.136Katarzyna Baraniak...
DL is built explicitly for dealing with significant amounts of data and performing complex tasks where automatic learning is a necessity. Thanks to its promise to detect complex patterns in a dataset, it may be appealing to those investors that are looking to improve their trading process. More...
"Sentiment Analysis on Financial News Headlines using Training Dataset Augmentation", Pro- ceedings of the 11th ... V John,O Vechtomova - International Workshop on Semantic Evaluation 被引量: 2发表: 2017年 Data Augmentation for Sentiment Analysis Using Sentence Compression-Based SeqGAN With Data ...
In this paper, we focus on studying sentiment analysis impact, on financial markets. Current studies, lack systematic approaches to evaluate the impact of a given sentiment dataset, in different financial contexts. We introduce a framework that encompasses models, processes, and a supporting software...
I have put in some examples below for reference -The above snippet is from the Amazon sentiment review dataset , where the original label was Neutral in both cases, whereas Cleanlab and Mechanical turk said it to be positive (which is correct).The above snippet is from the MNIST dataset, ...
Sentiment Analysis on Financial News Headlines using Training Dataset Augmentation This paper discusses the approach taken by the UWaterloo team to arrive at a solution for the Fine-Grained Sentiment Analysis problem posed by Task 5 of Se... V John,O Vechtomova 被引量: 2发表: 2017年 Sentiment...
If you use either the dataset or any of the VADER sentiment analysis tools (VADER sentiment lexicon or Python code for rule-based sentiment analysis engine) in your research, please cite the above paper. For example: Hutto, C.J. & Gilbert, E.E. (2014). VADER: A Parsimonious Rule-based...
There is a collection of sentiment analysis datasets assembled by the Interest Group on German Sentiment Analysis. However, to my knowlege, no german topic classification dataset is avaliable to the public. Due to grammatical differences between the English and the German language, a classifyer might...
The authors used a dataset of more than 900,000 news stories to test whether news can predict stock returns. They measured sentiment with a proprietary Tho... SL Heston,NR Sinha - 《Social Science Electronic Publishing》 被引量: 36发表: 2017年 Why We Watch the News: A Dataset for Explori...
It also allows us to observe other objects, such as relationships.The Columns tab is a great way to see whether you have any columns that are very large relative to others or the entire dataset. The following figure shows the columns view for the same model we saw in Figure 6.9. You ...