A Benchmark of Visual Storytelling in Social Media

Marcelino, Gonçalo; Semedo, David; Mourão, André; Blasi, Saverio; Mrak, Marta; Magalhães, João

doi:10.1145/3323873.3325047

Cited by 9 publications

(5 citation statements)

References 12 publications

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“…Each judge made evaluation separately without contacting two others. This approach is similar to [ 55 ]: JS = 0: the image is not relevant to the text; JS = 1: the image is relevant to the text; JS = 2: the image is highly relevant to the text. …”

Section: Materials and Methodsmentioning

confidence: 99%

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TIPS: A Framework for Text Summarising with Illustrative Pictures

Golec

Hachaj

Sokal

2021

Entropy

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We propose an algorithm to generate graphical summarising of longer text passages using a set of illustrative pictures (TIPS). TIPS is an algorithm using a voting process that uses results of individual “weak” algorithms. The proposed method includes a summarising algorithm that generates a digest of the input document. Each sentence of the text summary is used as the input for further processing by the sentence transformer separately. A sentence transformer performs text embedding and a group of CLIP similarity-based algorithms trained on different image embedding finds semantic distances between images in the illustration image database and the input text. A voting process extracts the most matching images to the text. The TIPS algorithm allows the integration of the best (highest scored) results of the different recommendation algorithms by diminishing the influence of images that are a disjointed part of the recommendations of the component algorithms. TIPS returns a set of illustrative images that describe each sentence of the text summary. Three human judges found that the use of TIPS resulted in an increase in matching highly relevant images to text, ranging from 5% to 8% and images relevant to text ranging from 3% to 7% compared to the approach based on single-embedding schema.

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Section: Materials and Methodsmentioning

confidence: 99%

“…Each judge made evaluation separately without contacting two others. This approach is similar to [55]:…”

Section: Evaluation and Comparison Of Image-text Matching Algorithmsmentioning

confidence: 99%

TIPS: A Framework for Text Summarising with Illustrative Pictures

Golec

Hachaj

Sokal

2021

Entropy

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“…Hullman et al adapt the term state in DDS as an informationally distinct scene [10]. Marcelino et al name this sequence of segments a visual storyline [11]. The elements of each scene may change through a stream of consecutive states while having their own separate storylines.…”

Section: Dds Scene and Layoutmentioning

confidence: 99%

A Design Language for Prototyping and Storyboarding Data-Driven Stories

Asgari,

Hurtut

2024

Applied Sciences

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Data-driven stories (DDS) are digital forms of storytelling that arrange data and visualizations to communicate a narrative of information to an audience. They have been growing rapidly over the past decades. As a result, a great degree of versatility appears in the forms of published DDS. The recent structures of DDS are more complex, respecting their arrangement, composition, features, and inner parts. In the current academic research, neither storytelling techniques nor any taxonomies suggest visual mechanisms to distinguish between different layouts, compositions, and arrangements. The lack of an expressive visual solution that integrates different parts of DDS under one structure prevents the authors from trying more alternative design paths in the story design process. In this proposed work, we unify all the constructing parts of DDS to define the narrative structure as a visually structured representation of the DDS narrative, which is formed and designed by their constructing elements. This solution proposes a design language consisting of a set of design rules that integrate the visual elements to represent the DDS narrative structure. Our evaluation of the audit process out of 100 DDS examples confirms that the design language is comprehensive, expressive, and versatile. Additionally, we developed DataStoryDesign, a system that incorporates this visual solution to facilitate prototyping and storyboarding DDS for a team of DDS authors. The preliminary result of the exploratory evaluation indicates that such a solution is effective in prototyping and storyboarding DDS. In addition, our findings confirmed that the existence of our design language improves the visual communication between different personas in the DDS production workflow.

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“…We use the definition by Marcelino et al [51], whereby every news "story" is composed of several story "segments." In a nutshell, we perform three tasks: 1) we identify segments using the GDELT dataset [42]; 2) we build a graph where news articles are nodes and edges are common segments discussed in them; and 3) we perform community detection on the graph to identify articles that discuss the same story.…”

Section: News Stories Identificationmentioning

confidence: 99%

A Multi-Platform Analysis of Political News Discussion and Sharing on Web Communities

Wang¹,

Zannettou²,

Blackburn³

et al. 2021

Preprint

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The news ecosystem has become increasingly complex, encompassing a wide range of sources with varying levels of trustworthiness, and with public commentary giving different spins to the same stories. In this paper, we present a multiplatform measurement of this ecosystem. We compile a list of 1,073 news websites and extract posts from four Web communities (Twitter, Reddit, 4chan, and Gab) that contain URLs from these sources. This yields a dataset of 38M posts containing 15M news URLs, spanning almost three years.We study the data along several axes, assessing the trustworthiness of shared news, designing a method to group news articles into stories, analyzing these stories are discussed, and measuring the influence various Web communities have in that. Our analysis shows that different communities discuss different types of news, with polarized communities like Gab and /r/The_Donald subreddit disproportionately referencing untrustworthy sources. We also find that fringe communities often have a disproportionate influence on other platforms w.r.t. pushing narratives around certain news, for example about political elections, immigration, or foreign policy.

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A Benchmark of Visual Storytelling in Social Media

Cited by 9 publications

References 12 publications

TIPS: A Framework for Text Summarising with Illustrative Pictures

TIPS: A Framework for Text Summarising with Illustrative Pictures

A Design Language for Prototyping and Storyboarding Data-Driven Stories

A Multi-Platform Analysis of Political News Discussion and Sharing on Web Communities

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