Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Classification of Signals01:30

Classification of Signals

1.5K
In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
1.5K
Central Tendency: Analysis01:10

Central Tendency: Analysis

573
Measures of central tendency are tools used in biostatistics to identify the average or center of a dataset. They offer a single representative value for understanding and summarizing data distribution.
The mean is one such measure, calculated by totaling all values in a dataset and dividing by the number of values. For instance, the mean blood pressure reading (120, 130, 140, 150) would be 135. However, the mean can be affected by extreme values or outliers.
The median, another measure,...
573
Effective Value of a Periodic Waveform01:07

Effective Value of a Periodic Waveform

1.3K
The concept of effective value, the root mean square (RMS) value, is crucial in understanding electrical circuits and power delivery. This idea emerges from the necessity to measure the effectiveness of a voltage or current source in supplying power to a resistive load.
The effective value of a periodic current represents the direct current (DC) that conveys the same average power to a resistor as the periodic current itself. This concept is crucial when assessing AC circuits. To determine the...
1.3K
BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

985
System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....
985
Relative Frequency Histogram01:14

Relative Frequency Histogram

6.6K
The relative frequency depicts the proportion of data points that have each value. The frequency tells the number of data points that have each value. Like the histogram, a relative frequency histogram also has the same shape with a horizontal scale (the x-axis), but the vertical scale (the y-axis) is marked with relative frequencies (percentages of the whole) instead of actual frequencies. A relative frequency histogram is a graphical representation of a frequency distribution where the...
6.6K
Basic Continuous Time Signals01:22

Basic Continuous Time Signals

744
Basic continuous-time signals include the unit step function, unit impulse function, and unit ramp function, collectively referred to as singularity functions. Singularity functions are characterized by discontinuities or discontinuous derivatives.
The unit step function, denoted u(t), is zero for negative time values and one for positive time values, exhibiting a discontinuity at t=0. This function often represents abrupt changes, such as the step voltage introduced when turning a car's...
744

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Lanthanum oxide-loaded bacterial cellulose film with antibacterial and antioxidant properties exhibiting real-time pH response for smart food preservation packaging.

International journal of biological macromolecules·2026
Same author

Research on occupant injury mitigation strategy for vehicle frontal collision based on integrated active-passive safety boundary constraints.

Accident; analysis and prevention·2026
Same author

Urban-rural disparities in child linear growth: a decomposition analysis of digital, physical, and socioeconomic environments in seven least-developed countries.

Journal of global health·2026
Same author

Plant Phosphatidylinositol Signalling Network in Cotton Resistance to Verticillium Wilt.

Plant, cell & environment·2026
Same author

Exploring Treatment Mechanisms of the Resilient, Empowered, Active Living-Telehealth (REAL-T) Intervention.

Canadian journal of occupational therapy. Revue canadienne d'ergotherapie·2026
Same author

Formulation Optimization, Multi-Component Compounding Mechanisms, and Regeneration Insights of a Waste Vegetable Oil-Based Bitumen Regenerant.

Materials (Basel, Switzerland)·2026

Related Experiment Video

Updated: Feb 27, 2026

Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method
08:42

Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method

Published on: September 3, 2021

3.6K

Weibo sentiments and stock return: A time-frequency view.

Yingying Xu1, Zhixin Liu1, Jichang Zhao1

  • 1School of Economics and Management, Beihang University, Beijing, China.

Plos One
|July 4, 2017
PubMed
Summary

Detailed social media sentiments from Sina Weibo are linked to China's stock market returns. Specific emotions like sadness show stronger connections, with the stock market influencing sentiments more than vice-versa.

More Related Videos

Examining Changes in HRV and Emotion Following Artmaking with Three Different Art Materials
06:24

Examining Changes in HRV and Emotion Following Artmaking with Three Different Art Materials

Published on: January 11, 2020

6.8K
Functional Near-Infrared Spectroscopy Hyperscanning Study in Psychological Counseling
06:04

Functional Near-Infrared Spectroscopy Hyperscanning Study in Psychological Counseling

Published on: January 17, 2025

1.7K

Related Experiment Videos

Last Updated: Feb 27, 2026

Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method
08:42

Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method

Published on: September 3, 2021

3.6K
Examining Changes in HRV and Emotion Following Artmaking with Three Different Art Materials
06:24

Examining Changes in HRV and Emotion Following Artmaking with Three Different Art Materials

Published on: January 11, 2020

6.8K
Functional Near-Infrared Spectroscopy Hyperscanning Study in Psychological Counseling
06:04

Functional Near-Infrared Spectroscopy Hyperscanning Study in Psychological Counseling

Published on: January 17, 2025

1.7K

Area of Science:

  • Computational social science
  • Financial econometrics
  • Behavioral finance

Background:

  • Understanding the interplay between public sentiment and financial markets is crucial for economic analysis.
  • Social media platforms like Sina Weibo offer vast, real-time data on public opinion.

Purpose of the Study:

  • To investigate the relationship between detailed social media sentiments and the Chinese stock market.
  • To determine the predictive power of microblog sentiments for stock returns.

Main Methods:

  • Machine learning for sentiment classification of Sina Weibo microblogs into five categories: anger, disgust, fear, joy, and sadness.
  • Wavelet analysis to examine the time-varying and frequency-specific linkages between sentiments and stock returns.

Main Results:

  • Positive correlations were found between detailed sentiments and stock returns, particularly since October 2014 at medium to high frequencies.
  • Sadness sentiment demonstrated a stronger association with stock returns compared to other sentiments.
  • Stock market performance predominantly led Weibo sentiments, rather than the reverse, in periods of significant linkage.
  • Detailed sentiments, unlike simple polarity, offer richer insights into market dynamics, with the market positively impacting bullishness and agreement.

Conclusions:

  • Granular sentiment analysis from social media provides valuable information for understanding stock market behavior.
  • The stock market influences public sentiment, but specific sentiments like agreement can also lead market movements, suggesting improved market certainty with reduced disagreement.