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Impression Management Techniques II: Ingratiation

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Ingratiation refers to deliberate behaviors aimed at increasing one’s attractiveness or likability to a target person, often for strategic interpersonal or social gain. This set of impression management tactics is especially prevalent in hierarchical contexts, where influencing someone with greater power or authority can yield significant benefits. Several distinct ingratiation strategies have been identified, each leveraging psychological cues to foster favor and affiliation.Opinion...

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Using impression data to improve models of online social influence.

Rui Liu¹, Kevin T Greene¹, Ruibo Liu¹

¹Department of Computer Science, Dartmouth College, Hannover, 03755, USA.

Scientific Reports

|August 17, 2021

Summary

Social media influence is driven more by content exposure (impressions) than active engagement (expressions). Our models reveal impressions are key to identifying influential accounts and understanding online dynamics.

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Area of Science:

Social media dynamics
Computational social science
Network analysis

Background:

Influence is crucial on social media, yet current research is limited by data focusing on expressions (likes, comments) over impressions (views).
Existing studies lack ground truth measures for true influence.
Understanding social media influence requires a comprehensive approach beyond observable engagement.

Purpose of the Study:

To develop and validate novel models of social media influence.
To investigate the relative importance of impressions versus expressions in driving influence.
To provide a more accurate method for identifying influential social media accounts.

Main Methods:

Implemented a social media simulation on an original web-based micro-blogging platform.
Developed three distinct influence models incorporating both expressions and impressions data.
Utilized simulated user data to test and compare model performance.

Main Results:

Impressions were found to be significantly more important drivers of influence than expressions.
The proposed models accurately identified the most influential accounts within the simulation.
Analysis revealed the emergence of a few highly influential accounts and the formation of opinion echo chambers.

Conclusions:

Impressions are a critical, often overlooked, factor in social media influence.
Accurate influence modeling requires integrating both exposure and engagement data.
This approach enhances understanding of key social media phenomena like opinion polarization.