Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Quantifying social influence in an online cultural market.

ABSTRACT: We revisit experimental data from an online cultural market in which 14,000 users interact to download songs, and develop a simple model that can explain seemingly complex outcomes. Our results suggest that individual behavior is characterized by a two-step process--the decision to sample and the decision to download a song. Contrary to conventional wisdom, social influence is material to the first step only. The model also identifies the role of placement in mediating social signals, and suggests that in this market with anonymous feedback cues, social influence serves an informational rather than normative role.

SUBMITTER: Krumme C

PROVIDER: S-EPMC3348939 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Quantifying social influence in an online cultural market.

Krumme Coco C Cebrian Manuel M Pickard Galen G Pentland Sandy S

PloS one 20120509 5

We revisit experimental data from an online cultural market in which 14,000 users interact to download songs, and develop a simple model that can explain seemingly complex outcomes. Our results suggest that individual behavior is characterized by a two-step process--the decision to sample and the decision to download a song. Contrary to conventional wisdom, social influence is material to the first step only. The model also identifies the role of placement in mediating social signals, and sugges ...[more]

PMID: 22590493

Similar Datasets

Quantifying the effects of social influence.

Project description:How do humans respond to indirect social influence when making decisions? We analysed an experiment where subjects had to guess the answer to factual questions, having only aggregated information about the answers of others. While the response of humans to aggregated information is a widely observed phenomenon, it has not been investigated quantitatively, in a controlled setting. We found that the adjustment of individual guesses depends linearly on the distance to the mean of all guesses. This is a remarkable, and yet surprisingly simple regularity. It holds across all questions analysed, even though the correct answers differ by several orders of magnitude. Our finding supports the assumption that individual diversity does not affect the response to indirect social influence. We argue that the nature of the response crucially changes with the level of information aggregation. This insight contributes to the empirical foundation of models for collective decisions under social influence.

| S-EPMC3584930 | biostudies-other

Quantifying the Economic and Cultural Biases of Social Media through Trending Topics.

Project description:Online social media has recently irrupted as the last major venue for the propagation of news and cultural content, competing with traditional mass media and allowing citizens to access new sources of information. In this paper, we study collectively filtered news and popular content in Twitter, known as Trending Topics (TTs), to quantify the extent to which they show similar biases known for mass media. We use two datasets collected in 2013 and 2014, including more than 300.000 TTs from 62 countries. The existing patterns of leader-follower relationships among countries reveal systemic biases known for mass media: Countries concentrate their attention to small groups of other countries, generating a pattern of centralization in which TTs follow the gradient of wealth across countries. At the same time, we find subjective biases within language communities linked to the cultural similarity of countries, in which countries with closer cultures and shared languages tend to follow each other's TTs. Moreover, using a novel methodology based on the Google News service, we study the influence of mass media in TTs for four countries. We find that roughly half of the TTs in Twitter overlap with news reported by mass media, and that the rest of TTs are more likely to spread internationally within Twitter. Our results confirm that online social media have the power to independently spread content beyond mass media, but at the same time social media content follows economic incentives and is subject to cultural factors and language barriers.

| S-EPMC4521871 | biostudies-literature

Social selection and peer influence in an online social network.

Project description:Disentangling the effects of selection and influence is one of social science's greatest unsolved puzzles: Do people befriend others who are similar to them, or do they become more similar to their friends over time? Recent advances in stochastic actor-based modeling, combined with self-reported data on a popular online social network site, allow us to address this question with a greater degree of precision than has heretofore been possible. Using data on the Facebook activity of a cohort of college students over 4 years, we find that students who share certain tastes in music and in movies, but not in books, are significantly likely to befriend one another. Meanwhile, we find little evidence for the diffusion of tastes among Facebook friends-except for tastes in classical/jazz music. These findings shed light on the mechanisms responsible for observed network homogeneity; provide a statistically rigorous assessment of the coevolution of cultural tastes and social relationships; and suggest important qualifications to our understanding of both homophily and contagion as generic social processes.

| S-EPMC3252911 | biostudies-literature

Spontaneous emergence of social influence in online systems.

Project description:Social influence drives both offline and online human behavior. It pervades cultural markets, and manifests itself in the adoption of scientific and technical innovations as well as the spread of social practices. Prior empirical work on the diffusion of innovations in spatial regions or social networks has largely focused on the spread of one particular technology among a subset of all potential adopters. Here we choose an online context that allows us to study social influence processes by tracking the popularity of a complete set of applications installed by the user population of a social networking site, thus capturing the behavior of all individuals who can influence each other in this context. By extending standard fluctuation scaling methods, we analyze the collective behavior induced by 100 million application installations, and show that two distinct regimes of behavior emerge in the system. Once applications cross a particular threshold of popularity, social influence processes induce highly correlated adoption behavior among the users, which propels some of the applications to extraordinary levels of popularity. Below this threshold, the collective effect of social influence appears to vanish almost entirely, in a manner that has not been observed in the offline world. Our results demonstrate that even when external signals are absent, social influence can spontaneously assume an on-off nature in a digital environment. It remains to be seen whether a similar outcome could be observed in the offline world if equivalent experimental conditions could be replicated.

| S-EPMC2972979 | biostudies-literature

Cultural influence of social information use in pedestrian road-crossing behaviours.

Project description:Social information use is common in a wide range of group-living animals, notably in humans. The role it plays in decision-making could be a key to understanding how social groups make collective decisions. The observation of road-crossing behaviours in the presence of other individuals is an ideal means to study the influence of social information on decision-making. This study investigated the influence of culture on social information used by pedestrians in a potentially dangerous scenario, namely road crossing. We scored the collective crossing of pedestrians at four locations in Nagoya (Japan) and three locations in Strasbourg (France). French pedestrians cross against the lights much more often (41.9%) than Japanese ones (2.1%). Individuals deciding to cross the road were strongly influenced by the behaviour and the presence of other pedestrians, especially in Japan, where a stronger conformism was noted. However, Japanese pedestrians were half as likely to be influenced by social information as their French counterparts when crossing at the red light, as they were more respectful of rules. Men show riskier behaviour than women (40.6% versus 25.7% of rule-breaking, respectively), deciding quickly and setting off earlier than women. Further related studies could help target specific preventive, culture-specific solutions for pedestrian safety.

| S-EPMC5367276 | biostudies-literature

Using impression data to improve models of online social influence.

Project description:Influence, the ability to change the beliefs and behaviors of others, is the main currency on social media. Extant studies of influence on social media, however, are limited by publicly available data that record expressions (active engagement of users with content, such as likes and comments), but neglect impressions (exposure to content, such as views) and lack "ground truth" measures of influence. To overcome these limitations, we implemented a social media simulation using an original, web-based micro-blogging platform. We propose three influence models, leveraging expressions and impressions to create a more complete picture of social influence. We demonstrate that impressions are much more important drivers of influence than expressions, and our models accurately identify the most influential accounts in our simulation. Impressions data also allow us to better understand important social media dynamics, including the emergence of small numbers of influential accounts and the formation of opinion echo chambers.

| S-EPMC8368058 | biostudies-literature

Analysis of contemporary value and influence of intangible cultural heritage based on online review mining.

Project description:PurposeThe development of new media has enabled intangible cultural heritage to be disseminated through online platforms and attracted the attention of many contemporary young people. Classification and discussion on the value of intangible cultural heritage is an important way to help the inheritance and dissemination.Design/methodology/approachReal online reviews were collected based on the Bilibili website as the research data source. A text-based BiGRU-Attention model was conducted to achieve value recognition and classification, and keyword statistics and topic analysis were performed for topic discussion among comments.FindingsUsing the BiGRU-Attention model to classify intangible cultural heritage's contemporary values has a performance with precision, recall, and F1 score of more than 77%, the category of CVP (Cultural Value Perception) has the best classification performance. Through the topic analysis of comments and keywords, the cultural value of intangible cultural heritage is its core connotation, social value is the main purpose, and economic value is the power source.OriginalityA BiGRU-Attention model based on BERT word embedding is proposed to achieve a text contemporary value perception recognition method based on user-generated content.

| S-EPMC11658534 | biostudies-literature

Quantifying the visual-sensory landscape qualities that contribute to cultural ecosystem services using social media and LiDAR.

Project description:Landscapes are increasingly recognized for providing valuable cultural ecosystem services with numerous non-material benefits by serving as places of rest, relaxation, and inspiration that ultimately improve overall mental health and physical well-being. Maintaining and enhancing these valuable benefits through targeted management and conservation measures requires understanding the spatial and temporal determinants of perceived landscape values. Content contributed through mobile technologies and the web are emerging globally, providing a promising data source for localizing and assessing these landscape benefits. These georeferenced data offer rich in situ qualitative information through photos and comments that capture valued and special locations across large geographic areas. We present a novel method for mapping and modeling landscape values and perceptions that leverages viewshed analysis of georeferenced social media data. Using a high resolution LiDAR (Light Detection and Ranging) derived digital surface model, we are able to evaluate landscape characteristics associated with the visual-sensory qualities of outdoor recreationalists. Our results show the importance of historical monuments and attractions in addition to specific environmental features which are appreciated by the public. Evaluation of photo-image content highlights the opportunity of including temporally and spatially variable visual-sensory qualities in cultural ecosystem services (CES) evaluation like the sights, sounds and smells of wildlife and weather phenomena.

| S-EPMC6104849 | biostudies-literature

Quantifying Wikipedia Usage Patterns Before Stock Market Moves

Project description:Financial crises result from a catastrophic combination of actions. Vast stock market datasets offer us a window into some of the actions that have led to these crises. Here, we investigate whether data generated through Internet usage contain traces of attempts to gather information before trading decisions were taken. We present evidence in line with the intriguing suggestion that data on changes in how often financially related Wikipedia pages were viewed may have contained early signs of stock market moves. Our results suggest that online data may allow us to gain new insight into early information gathering stages of decision making.

| S-EPMC3647164 | biostudies-literature

Social influence makes outlier opinions in online reviews offer more helpful information.

Project description:Identifying helpful information from large-scale online reviews has become a core issue in studies on harnessing wisdom-of-crowds. We investigated whether online reviews expressing dissenting opinions (i.e., outlier reviews) can provide helpful information. Using statistical and simulation methods with a large-scale dataset, we found that, compared with other online reviews, outlier reviews were deemed more helpful because they provided more sufficient, neutral, and concise information. To interpret these results, we considered that in collective behaviours, a prevalent social psychological process-conformity (i.e., changing one's behaviour in response to pressure from others)-pressured reviewers expressing dissenting opinions. This motivated them to provide more convincing evidence (i.e., sufficient, neutral, and concise information). This study offers a simple yet effective approach for eliciting helpful information from many online reviews and deepens the understanding of the mechanism underlying collective online behaviour. Specifically, conformity was considered to cause biases in the collective behaviour of humans; however, this study revealed that conformity can elicit valuable outcomes in collective behaviour.

| S-EPMC10300035 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data