Related Experiment Video
Updated: Jul 29, 2025

13:51
Cross-Modal Multivariate Pattern Analysis
Published on: November 9, 2011
20.0K
Understanding image-text relations and news values for multimodal news analysis
Gullal S Cheema1, Sherzod Hakimov2, Eric Müller-Budack1,3
1TIB - Leibniz Information Centre for Science and Technology, Hannover, Germany.
Frontiers in Artificial Intelligence
|May 19, 2023
Summary
This study introduces a new computational framework for analyzing multimodal news, enhancing the detection of disinformation and misinformation. The framework integrates semiotics, machine learning, and journalism studies for scalable news analysis.
Area of Science:
- Computational social science
- Multimodal machine learning
- Digital humanities
Background:
- The increasing prevalence of multimodal online news necessitates advanced computational methods for analysis and credibility assessment.
- Existing multimodal machine learning excels at basic image-text correspondences but falls short for complex news analysis.
- Identifying disinformation and misinformation in news requires scalable computational approaches.
Discussion:
- This paper proposes a novel framework for computational analysis of multimodal news, moving beyond simple descriptive relations.
- The framework incorporates complex image-text relations and multimodal news values, drawing from semiotics and journalism studies.
- It bridges the gap between existing literature on image-text relations and computational models derived from data.
Key Insights:
- A new framework for multimodal news analysis is presented, integrating semiotics, computational linguistics, and journalism studies.
- The framework enables the computational analysis of complex image-text relations and news values.
- This approach enhances the identification of disinformation and misinformation in online news.
Outlook:
- Future research can leverage this framework at the intersection of multimodal learning, analytics, and computational social sciences.
- Applications include developing more sophisticated tools for news credibility assessment and media analysis.
- This work paves the way for advanced computational approaches to understanding news dissemination.
Keywords:
computational analyticsimage-text relationsjournalismmachine learningmultimodalitynews analysisnews valuessemioticsMore Related Videos
Related Concept Videos
Attribution Theory
13.1K
Behavior is a product of both the situation (e.g., cultural influences, social roles, and the presence of bystanders) and of the person (e.g., personality characteristics). Subfields of psychology tend to focus on one influence or behavior over others. Situationism is the view that our behavior and actions are determined by our immediate environment and surroundings. In contrast, dispositionism holds that our behavior is determined by internal factors (Heider, 1958).
13.1K
The Representativeness Heuristic
15.9K
The representative heuristic describes a biased way of thinking, in which you unintentionally stereotype someone or something. For example, you may assume that your professors spend their free time reading books and engaging in intellectual conversation, because the idea of them spending their time playing volleyball or visiting an amusement park does not fit in with your stereotypes of professors.
15.9K
Sensory Modalities
1.4K
Sensation typically is the process by which the sensory receptors and sense organs detect stimuli from the internal and external environment and transmit this information to the central nervous system for processing.
General senses refer to the broad category of sensory information detected by receptors in the body and can be further grouped into somatic and visceral senses. Somatic sensations include touch, pressure, temperature, and pain and are essential for navigating our environment and...
General senses refer to the broad category of sensory information detected by receptors in the body and can be further grouped into somatic and visceral senses. Somatic sensations include touch, pressure, temperature, and pain and are essential for navigating our environment and...
1.4K
Stereotype Content Model
14.8K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
14.8K
Hindsight Biases
3.5K
Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Can you relate this to the phrase "Hindsight is 20/20" now?
3.5K
Classification of Signals
560
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...
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...
560

