Drivers of News Sharing
How Context, Content, and User Features Shape Sharing Decisions on Facebook
Bibliographic Data
| ID | 22010648 |
|---|---|
| Authors | Damian Trilling (0000-0002-2586-0352, University of Bergen), Erik Knudsen (0000-0002-7046-9424, University of Bergen, corresponding author) |
| Year | 2025 |
| Volume | 13 |
| Issue | 4 |
| Pages | 723-744 |
| Publication date | 2025-04-21 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Digital Journalism (JOURNAL) |
| Journal identifiers | ISSN: 2167-0811 • E-ISSN: 2167-082X |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/21670811.2023.2255224 |
| OpenAlex | W4386957458 |
| Language | EN |
| Citations received | 5 |
| References cited | 51 |
What makes people share political news on Facebook? Prior studies have identified how different features predict audiences’ likelihood to share news on social media – the so-called shareworthiness of news. However, we still know very little about the relative contributions of these different features for predicting why people decide to share news. We extend the literature by using an experimental design that can compare the relative importance of several key features that contribute to shaping citizens’ sharing decisions: a conjoint experimental design. We use an identical layout to Facebook and a probability sample of Norwegian citizens. We find that particularly content characteristics are important, and that popularity cues and message congruence is conditional on some user characteristics such as age
Advertising · Business · Internet privacy · Norwegian · Political science · Politics · Popularity · Social media · User-generated content · World Wide Web · Computer Science · Media Studies and Communication · Opinion Dynamics and Social Influence · Psychology · Social Media and Politics · Social Psychology
Can AI-Attributed News Challenge Partisan News Selection? Evidence from a Conjoint Experiment
Waves of Attention to Racial Injustice on Social Media
Information and news use by older adults in social media and messenger apps
Social media filtering of sensationalistic news on spiders—A global overview
Engagement with Mainstream Media Political News on Facebook Among Youth in Nigeria
The Rationalizing Voter
Republic
Republic
Selective Exposure in the Age of Social Media
Effective Headlines of Newspaper Articles in a Digital Environment
Impact of Popularity Indications on Readers' Selective Exposure to Online News
From Newsworthiness to Shareworthiness
Exposure to ideologically diverse news and opinion on Facebook
The Oxford Handbook of Political Communication
Broadcast Versus Viral Spreading
You Should Read This Study! It Investigates Scandinavian Social Media Logics ☝
Shareworthiness and Motivated Reasoning in Hyper-Partisan News Sharing Behavior on Twitter
Disentangling the Influence of Recommender Attributes and News-Story Attributes
Optimizing Content with A/B Headline Testing
I like what I see
Behavioral Effects of Framing on Social Media Users
Implicit and Explicit Attitudes as Predictors of Gatekeeping, Selective Exposure, and News Sharing
Selective Use of News Cues
Partisan Selective Sharing
Social and Heuristic Approaches to Credibility Evaluation Online
Popularity cues in online media
News Sharing in Social Media
Exploring Engagement With EU News on Facebook
Facebook News Use During the 2017 Norwegian Elections—Assessing the Influence of Hyperpartisan News
Reuters Institute Digital News Report 2015
What Affects First- and Second-Level Selective Exposure to Journalistic News? A Social Media Online Experiment
To Share or Not to Share
Discussions in the comments section
Clickbait news and algorithmic curation
Six Uses of Analytics
Audience Metrics
Good News and Bad News
Choosing to Avoid? A Conjoint Experimental Study to Understand Selective Exposure and Avoidance on Social Media
Beyond the Limits of Survey Experiments
Measuring Subgroup Preferences in Conjoint Experiments
Causal Inference in Conjoint Analysis
Media and Political Polarization
The Hidden American Immigration Consensus
Curated Flows
Feeling validated versus being correct
Why Do People Share Ideologically Extreme, False, and Misleading Content on Social Media? A Self-Report and Trace Data-Based Analysis of Countermedia Content Dissemination on Facebook and Twitter
| Unique citing works | 5 |
|---|---|
| Citations per year | 5 |
| Citation span | 2025 - 2026 (2) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 5 |