In particular, cascades without positive content tend to be larger, and their size follows a qualitatively different distribution.
This is consistent with our finding that cascades with higher social content activate larger amounts of participants.
Power-law fits indicate that the distribution of the size of activity cascades with high social content have an exponent of (alpha=1.87pm0.09), while the distribution for low social content has an exponent of (2.33pm0.07).
In this case, however, information cascades with high social content exhibit a power-law behavior with exponent (alpha=1.66pm0.01), which indicates that the expected size scales with the system size.
The outcome is not so clear for low social content information cascades, for which (alpha=1.98pm0.02) is compatible with 2. However, the latter are best described by a log-normal distribution, as suggested by the log-likelihood ratio R, and the expected size of the audience does not scale with the system size (details on these fits can be found in Additional file 1, Table X).
The Rhodophyta include taxa with some or all of their cells being multinucleate or endopolyploid (Kapraun and Nguyen 1994; Kapraun 2005) as well as taxa that exhibit a nuclear 'incremental size decrease associated with a cascading down of DNA contents' (Kapraun 1994).
On the other hand, our analysis of social content in the cascades reveals a clear pattern: cascades with large ratios of social-related terms have distributions of listener and spreader sizes that scale with system size, in contrast with cascades with low ratios of social-related terms, which follow distributions that have bounded means.
Topic Cascade [4], on the other hand, directly integrates the extracted topic distribution from the textual content of diffused cascades to infer the network, which is viewed as topic sensitive.
Figure 2 CCDF of activity (left) and information (right) cascade sizes for cascades of high and low social content (top) and high and low cognitive content (bottom).
Users belonging to different communities tended not to interact and tended to be connected only with "like-minded" friends, creating closed, non-interacting communities centered around different narratives — what the researchers called "echo chambers". Confirmation bias accounted for users' decisions to share certain content, creating informational cascades within their communities.
For Peak and Increasing classes, the number of reposts received,cascade size and followers increases significantly in CP compared toBefore (Figure 5(d), (e), (f) respectively).Since reposts received and cascade size are proxies for content interestingness, thisindicates the production of content that attracts the attention of a much highernumber of users.
