ArticlePloS one2019
Individual EEG measures of attention, memory, and motivation predict population level TV viewership and Twitter engagement.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
19 citing papers in PubMed, 74 citations in OpenAlex.
- Article
- Perspective-taking in video advertising: insights from EEG connectivity and channel-wise spectral analysis.Frontiers in behavioral neuroscience · 2026Article
- Measuring Realistic Emotional Perception With EEG: A Comparison of Multimodal Videos and Naturalistic Scenes.Psychophysiology · 2025Article
- Predicting attachment style from EEG data on the Flanker task.Frontiers in human neuroscience · 2025Article
- Radio, Podcasts, and Music Streaming-An Electroencephalography and Physiological Analysis of Listeners' Attitude, Attention, Memory, and Engagement.Brain sciences · 2024Article
- Increased EEG gamma power under exposure to drug-related cues: a translational index for cue-elicited craving in METH-dependent individuals.BMC psychiatry · 2023Article
- Spatiotemporal consistency of neural responses to repeatedly presented video stimuli accounts for population preferences.Scientific reports · 2023Article
- A Sparse Representation Classification Scheme for the Recognition of Affective and Cognitive Brain Processes in Neuromarketing.Sensors (Basel, Switzerland) · 2023Article
- DeePay: deep learning decodes EEG to predict consumer's willingness to pay for neuromarketing.Frontiers in human neuroscience · 2023Article
- EEG and peripheral markers of viewer ratings: a study of short films.Frontiers in neuroscience · 2023Article
- Coding peekaboom: a gaming mechanism for harvesting programming concepts.Education and information technologies · 2023Article
- Consumer Behaviour to Be Considered in Advertising: A Systematic Analysis and Future Agenda.Behavioral sciences (Basel, Switzerland) · 2022Review
- A systematic review of the prediction of consumer preference using EEG measures and machine-learning in neuromarketing research.Brain informatics · 2022Review
- Decoding the neural signatures of valence and arousal from portable EEG headset.Frontiers in human neuroscience · 2022Article
- Mind the gap: State-of-the-art technologies and applications for EEG-based brain-computer interfaces.APL bioengineering · 2021Review
- Cognitive Neuroscience Methods in Enhancing Health Literacy.International journal of environmental research and public health · 2021Article
- A Sound Prediction: EEG-Based Neural Synchrony Predicts Online Music Streams.Frontiers in psychology · 2021Article
- Investigating the Use of Pretrained Convolutional Neural Network on Cross-Subject and Cross-Dataset EEG Emotion Recognition.Sensors (Basel, Switzerland) · 2020Article
- Comparison between a wireless dry electrode EEG system with a conventional wired wet electrode EEG system for clinical applications.Scientific reports · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
Television (TV) programming attracts ever-growing audiences and dominates the cultural zeitgeist. Viewership and social media engagement have become standard indices of programming success. However, accurately predicting individual episode success or future show performance using traditional metrics remains a challenge. Here we examine whether TV viewership and Twitter activity can be predicted using electroencephalography (EEG) measures, which are less affected by reporting biases and which are commonly associated with different cognitive processes. 331 participants watched an hour-long episode from one of nine prime-time shows (~36 participants per episode). Three frequency-based measures were extracted: fronto-central alpha/beta asymmetry (indexing approach motivation), fronto-central alpha/theta power (indexing attention), and fronto-central theta/gamma power (indexing memory processing). All three EEG measures and the composite EEG score significantly correlated across episode segments with the two behavioral measures of TV viewership and Twitter volume. EEG measures explained more variance than either of the behavioral metrics and mediated the relationship between the two. Attentional focus was integral for both audience retention and Twitter activity, while emotional motivation was specifically linked with social engagement and program segments with high TV viewership. These findings highlight the viability of using EEG measures to predict success of TV programming and identify cognitive processes that contribute to audience engagement with television shows.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.