Selecting training sets for support vector machines: a review
Support vector machines (SVMs) are a supervised classifier successfully applied in a
plethora of real-life applications. However, they suffer from the important shortcomings of …
plethora of real-life applications. However, they suffer from the important shortcomings of …
Sarcasm detection using machine learning algorithms in Twitter: A systematic review
SM Sarsam, H Al-Samarraie… - … Journal of Market …, 2020 - journals.sagepub.com
Recognizing both literal and figurative meanings is crucial to understanding users' opinions
on various topics or events in social media. Detecting the sarcastic posts on social media …
on various topics or events in social media. Detecting the sarcastic posts on social media …
A hybrid model integrating deep learning with investor sentiment analysis for stock price prediction
N Jing, Z Wu, H Wang - Expert Systems with Applications, 2021 - Elsevier
Whether stock prices are predictable has been the center of debate in academia. In this
paper, we propose a hybrid model that combines a deep learning approach with a sentiment …
paper, we propose a hybrid model that combines a deep learning approach with a sentiment …
A model for sentiment and emotion analysis of unstructured social media text
Sentiment analysis has applications in diverse contexts such as in the gathering and
analysis of opinions of individuals about various products, issues, social, and political …
analysis of opinions of individuals about various products, issues, social, and political …
A glimpse on big data analytics in the framework of marketing strategies
Mining and analyzing the valuable knowledge hidden behind the amount of data available
in social media is becoming a fundamental prerequisite for any effective and successful …
in social media is becoming a fundamental prerequisite for any effective and successful …
[HTML][HTML] Data science, machine learning and big data in digital journalism: A survey of state-of-the-art, challenges and opportunities
Digital journalism has faced a dramatic change and media companies are challenged to use
data science algorithms to be more competitive in a Big Data era. While this is a relatively …
data science algorithms to be more competitive in a Big Data era. While this is a relatively …
Sentiment analysis on E-sports for education curriculum using naive Bayes and support vector machine
The development of e-sports education is not just playing games, but about start making,
development, marketing, research and other forms education aimed at training skills and …
development, marketing, research and other forms education aimed at training skills and …
SACPC: A framework based on probabilistic linguistic terms for short text sentiment analysis
C Song, XK Wang, P Cheng, J Wang, L Li - Knowledge-Based Systems, 2020 - Elsevier
Short text sentiment analysis is challenging because short texts are limited in length and
lack context. Short texts are usually rather ambiguous because of polysemy and the typos …
lack context. Short texts are usually rather ambiguous because of polysemy and the typos …
Detecting customers knowledge from social media big data: toward an integrated methodological framework based on netnography and business analytics
P Del Vecchio, G Mele, G Passiante… - Journal of Knowledge …, 2020 - emerald.com
Purpose This paper aims to demonstrate how the integration of netnography and business
analytics can support companies in the process of value creation from social big data by …
analytics can support companies in the process of value creation from social big data by …
Sentiment analysis and spam detection in short informal text using learning classifier systems
Sentiment analysis of public views and spam detection from social media text messages are
two challenging data analysis tasks due to short informal text. This paper investigates the …
two challenging data analysis tasks due to short informal text. This paper investigates the …