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Rescooped by Jean-Michel Livowsky from Influence et contagion
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The six types of Twitter conversations | #patterns #archetypes

The six types of Twitter conversations | #patterns #archetypes | Intelligence | Scoop.it
Have you ever wondered what a Twitter conversation looks like from 10,000 feet?

Via Pierre Levy, luiy
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luiy's curator insight, March 25, 2014 2:20 PM

Have you ever wondered what a Twitter conversation looks like from 10,000 feet? A new report from the Pew Research Center, in association with the Social Media Research Foundation, provides an aerial view of the social media network. By analyzing many thousands of Twitter conversations, we identified six different conversational archetypes. Our infographic describes each type of conversation network and an explanation of how it is shaped by the topic being discussed and the people driving the conversation.

Kamian's curator insight, March 26, 2014 11:57 PM

Me encantan estas clasificaciones, ayudan a comprender y diferenciar rapidamente las diferentes dinámicas sociales y arquitecturas que se van conformando en las redes sociales.

Rescooped by Jean-Michel Livowsky from e-Xploration
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Looking at Culture through a Big Data Lens I #patterns #memes

Looking at Culture through a Big Data Lens I #patterns #memes | Intelligence | Scoop.it
I’m excited about all the (possible) breakthroughs we see happening in cultural research.

Via luiy
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luiy's curator insight, December 26, 2013 9:06 PM

Predicting by looking at narratives


Other Big Data cultural research examples will be presented tomorrow at a conference organized by the Dutch Meertens Institute “Patterns in narrative texts“. The data that will be discussed range from narrative journalistic texts to orally transmitted folktales. In the study of history, diachronic corpora can be mined to discover how historical events are reflected in language use. In folk narrative research, patterns of interest include the stability and variability of ‘narrative building blocks’ (motifs, memes) in oral transmission, and geographical dispersion of folk beliefs in the supernatural. Establishing links between narrative texts is a common factor in all this research.

 

One of the pieces of research that will be discussed is “Mining the Twentieth Century’s History from the TIME Magazine Corpus”. Mike Kestemont & Folgert Karsdorp are going to explain how to predict Times’s Person of the Year. In their research they have paid special attention to the intriguing interplay between this list of influential personalities and the manner in which they are discussed in the magazine’s own archive. They will have a lot to explain, looking at their top-10 list for 2013, since they’ve missed the person that has won this year, Pope Fransicus. But still the researchers have a hit-rate of more than 20%.

Rescooped by Jean-Michel Livowsky from Influence et contagion
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Time varying networks and the weakness of strong ties | #patterns #rumor #SNA

Time varying networks and the weakness of strong ties | #patterns #rumor #SNA | Intelligence | Scoop.it

In most social and information systems the activity of agents generates rapidly evolving time-varying networks. The temporal variation in networks' connectivity patterns and the ongoing dynamic processes are usually coupled in ways that still challenge our mathematical or computational modelling. Here we analyse a mobile call dataset and find a simple statistical law that characterize the temporal evolution of users' egocentric networks. We encode this observation in a reinforcement process defining a time-varying network model that exhibits the emergence of strong and weak ties. We study the effect of time-varying and heterogeneous interactions on the classic rumour spreading model in both synthetic, and real-world networks. We observe that strong ties severely inhibit information diffusion by confining the spreading process among agents with recurrent communication patterns. This provides the counterintuitive evidence that strong ties may have a negative role in the spreading of information across networks.


Via luiy
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