Dimensionality of Social Networks Using Motifs and Eigenvalues

We consider the dimensionality of social networks, and develop experiments aimed at predicting that dimension. We find that a social network model with nodes and links sampled from an m-dimensional metric space with power-law distributed influence regions best fits samples from real-world networks when m scales logarithmically with the number of nodes of the network. This supports a logarithmic dimension hypothesis, and we provide evidence with two different social networks, Facebook and LinkedIn. Further, we employ two different methods for confirming the hypothesis: the first uses the distribution of motif counts, and the second exploits the eigenvalue distribution.     

Bringing Elton and Grinnell together: a quantitative framework to represent the biogeography of ecological interaction networks

Biogeography has traditionally focused on the spatial distribution and abundance of species. Both are driven by the way species interact with one another, but only recently community ecologists realized the need to document their spatial and temporal variation. Here, we call for an integrated approach, adopting the view that community structure is best represented as a network of ecological interactions, and show how it translates to biogeography questions. We propose that the ecological niche should encompass the effect of the environment on species distribution (the Grinnellian dimension of the niche) and on the ecological interactions among them (the Eltonian dimension). Starting from this concept, we develop a quantitative theory to explain turnover of interactions in space and time – i.e. a novel approach to interaction distribution modeling. We apply this framework to host–parasite interactions across Europe and find that two aspects of the environment (temperature and precipitation) exert a strong imprint on species co‐occurrence, but not on species interactions. Even where species co‐occur, interaction proves to be stochastic rather than deterministic, adding to variation in realized network structure. We also find that a large majority of host‐parasite pairs are never found together, thus precluding any inferences regarding their probability to interact. This first attempt to explain variation of network structure at large spatial scales opens new perspectives at the interface of species distribution modeling and community ecology.     

Diffusion of Messages from an Electronic Cigarette Brand to Potential Users through Twitter

Objective

This study explores the presence and actions of an electronic cigarette (e-cigarette) brand, Blu, on Twitter to observe how marketing messages are sent and diffused through the retweet (i.e., message forwarding) functionality. Retweet networks enable messages to reach additional Twitter users beyond the sender’s local network. We follow messages from their origin through multiple retweets to identify which messages have more reach, and the different users who are exposed.

Methods

We collected three months of publicly available data from Twitter. A combination of techniques in social network analysis and content analysis were applied to determine the various networks of users who are exposed to e-cigarette messages and how the retweet network can affect which messages spread.

Results

The Blu retweet network expanded during the study period. Analysis of user profiles combined with network cluster analysis showed that messages of certain topics were only circulated within a community of e-cigarette supporters, while other topics spread further, reaching more general Twitter users who may not support or use e-cigarettes.

Conclusions

Retweet networks can serve as proxy filters for marketing messages, as Twitter users decide which messages they will continue to diffuse among their followers. As certain e-cigarette messages extend beyond their point of origin, the audience being exposed expands beyond the e-cigarette community. Potential implications for health education campaigns include utilizing Twitter and targeting important gatekeepers or hubs that would maximize message diffusion.     

Quantifying Regional Differences in the Length of Twitter Messages

The increasing usage of social media for conversations, together with the availability of its data to researchers, provides an opportunity to study human conversations on a large scale. Twitter, which allows its users to post messages of up to a limit of 140 characters, is one such social media. Previous studies of utterances in books, movies and Twitter have shown that most of these utterances, when transcribed, are much shorter than 140 characters. Furthermore, the median length of Twitter messages was found to vary across US states. Here, we investigate whether the length of Twitter messages varies across different regions in the UK. We find that the median message length, depending on grouping, can differ by up to 2 characters.     

Performance of Social Network Sensors during Hurricane Sandy

Information flow during catastrophic events is a critical aspect of disaster management. Modern communication platforms, in particular online social networks, provide an opportunity to study such flow and derive early-warning sensors, thus improving emergency preparedness and response. Performance of the social networks sensor method, based on topological and behavioral properties derived from the “friendship paradox”, is studied here for over 50 million Twitter messages posted before, during, and after Hurricane Sandy. We find that differences in users’ network centrality effectively translate into moderate awareness advantage (up to 26 hours); and that geo-location of users within or outside of the hurricane-affected area plays a significant role in determining the scale of such an advantage. Emotional response appears to be universal regardless of the position in the network topology, and displays characteristic, easily detectable patterns, opening a possibility to implement a simple “sentiment sensing” technique that can detect and locate disasters.     

Not looking where you are leaping: a novel method of oriented travel in the caterpillar Calindoea trifascialis (Moore) (Lepidoptera: Thyrididae)

The prepupation caterpillar of the Southeast Asian moth Calindoea trifascialis constructs a leaf shelter that jumps across the ground using a jumping method novel among the insects. We found that movement path direction was correlated to the direction opposite to the most intense light. Correlated random walk (CRW) analyses found net squared displacements higher than predicted by a CRW, and fractal dimension analysis indicated straighter paths at large spatial scales. Rearing experiments showed high mortality from predation on the ground, but higher mortality resulted from sun exposure. We interpret jumping path orientation as an efficient search strategy to find shade in a variable landscape, given limited perception, in the presence of overheating and desiccation risks.     

Participation and Contribution in Crowdsourced Surveys

This paper identifies trends within and relationships between the amount of participation and the quality of contributions in three crowdsourced surveys. Participants were asked to perform a collective problem solving task that lacked any explicit incentive: they were instructed not only to respond to survey questions but also to pose new questions that they thought might-if responded to by others-predict an outcome variable of interest to them. While the three surveys had very different outcome variables, target audiences, methods of advertisement, and lengths of deployment, we found very similar patterns of collective behavior. In particular, we found that: the rate at which participants submitted new survey questions followed a heavy-tailed distribution; the distribution in the types of questions posed was similar; and many users posed non-obvious yet predictive questions. By analyzing responses to questions that contained a built-in range of valid response we found that less than 0.2% of responses lay outside of those ranges, indicating that most participants tend to respond honestly to surveys of this form, even without explicit incentives for honesty. While we did not find a significant relationship between the quantity of participation and the quality of contribution for both response submissions and question submissions, we did find several other more nuanced participant behavior patterns, which did correlate with contribution in one of the three surveys. We conclude that there exists an optimal time for users to pose questions early on in their participation, but only after they have submitted a few responses to other questions. This suggests that future crowdsourced surveys may attract more predictive questions by prompting users to pose new questions at specific times during their participation and limiting question submission at non-optimal times.     

Seeing through the static: the temporal dimension of plant–animal mutualistic interactions

Most studies of plant–animal mutualistic networks have come from a temporally static perspective. This approach has revealed general patterns in network structure, but limits our ability to understand the ecological and evolutionary processes that shape these networks and to predict the consequences of natural and human‐driven disturbance on species interactions. We review the growing literature on temporal dynamics of plant–animal mutualistic networks including pollination, seed dispersal and ant defence mutualisms. We then discuss potential mechanisms underlying such variation in interactions, ranging from behavioural and physiological processes at the finest temporal scales to ecological and evolutionary processes at the broadest. We find that at the finest temporal scales (days, weeks, months) mutualistic interactions are highly dynamic, with considerable variation in network structure. At intermediate scales (years, decades), networks still exhibit high levels of temporal variation, but such variation appears to influence network properties only weakly. At the broadest temporal scales (many decades, centuries and beyond), continued shifts in interactions appear to reshape network structure, leading to dramatic community changes, including loss of species and function. Our review highlights the importance of considering the temporal dimension for understanding the ecology and evolution of complex webs of mutualistic interactions.     

黄河三角洲滨海湿地芦苇、碱蓬混生群落空间点格局分析

为了解黄河三角洲滨海湿地芦苇、碱蓬群落内的种群相互关系、多样的生态策略, 通过重复取样的调查方法, 运用多种汇总统计函数分析了黄河入海口处以黄河河道为基轴向北延伸至海边的三个不同区域的芦苇和碱蓬混生种群的种群结构和空间点格局。结果表明: 黄河边碱蓬和芦苇在全部尺度上趋于聚集分布; 中部滩涂湿地碱蓬在2-35 cm尺度上呈现聚集分布, 在1cm以及36-45cm尺度上呈现随机分布, 在其他尺度呈现均匀分布,芦苇在3-4 cm以及15 cm、20 cm尺度上呈现聚集分布, 其他尺度上呈现随机分布; 近海区域碱蓬在全部尺度上呈现随机分布, 芦苇在0-16 cm、21-25 cm以及44-46 cm尺度上呈现随机分布, 在其他尺度呈现聚集分布。黄河边芦苇和碱蓬种群种间关系趋于负相关, 种群之间相互排斥, 在中部滩涂湿地和近海区域两种群无关联, 仅在近海区域28-31 cm尺度出现正相关关系。黄河边两种植物的点格局分布以及种间关系与其他两个区域存在明显差异,需进一步开展相关实验深入了解黄河三角洲滨海湿地环境因素对芦苇、碱蓬混生群落点格局的影响。     

Does the Type of Event Influence How User Interactions Evolve on Twitter?

The number of people using on-line social networks as a new way of communication is continually increasing. The messages that a user writes in these networks and his/her interactions with other users leave a digital trace that is recorded. Thanks to this fact and the use of network theory, the analysis of messages, user interactions, and the complex structures that emerge is greatly facilitated. In addition, information generated in on-line social networks is labeled temporarily, which makes it possible to go a step further analyzing the dynamics of the interaction patterns. In this article, we present an analysis of the evolution of user interactions that take place in television, socio-political, conference, and keynote events on Twitter. Interactions have been modeled as networks that are annotated with the time markers. We study changes in the structural properties at both the network level and the node level. As a result of this analysis, we have detected patterns of network evolution and common structural features as well as differences among the events.     

The names of Spain: a study of the isonymy structure of Spain

In order to estimate the isonymy structure of Spain, we studied surname distribution in 283 Spanish towns based on 3.625 million telephone users selected from 6.328 million users, downloaded from a commercial CD-ROM which contains all 13 million users in the country. Since in Spain the surname is made by the paternal and the maternal surname, it was possible to classify surnames according to parental origin. Two matrices of isonymy distances, one for paternal and one for maternal surnames, were constructed and tested for correlation with geographic distance. For the whole of Spain, Euclidean distance was significantly but weakly correlated with geographic distance both for paternal and maternal surnames, with r = 0.205 +/- 0.013 and r = 0.263 +/- 0.012, respectively. Two dendrograms of the 283 sampled towns were built from the two matrices of Euclidean distance. They are largely colinear. Four main clusters identified by the dendrograms are correlated with geography. Given the surname structure of Spain, we were able to calculate from isonymy and for each town 1). total or expressed inbreeding, 2). random or expected inbreeding, and 3). local inbreeding. Total inbreeding, F(IT), was highest in the North Atlantic regions and lowest along the Mediterranean Coast. The lowest levels were found in Andalusia, Catalunyia, Valencia, and Navarra. Random inbreeding, F(ST), had a similar geographical pattern. Local inbreeding, F(IS), was relatively uniform in the whole of Spain. In towns, random inbreeding dominates over local inbreeding. From the analysis, it emerges that the northwestern area of Spain is the most inbred.     

A histochemical study of keratinization in the domestic fowl (Gallus gallus)

The microanatomy of the epidermis of the domestic fowl is described and related to the distribution of various histochemical constituents involved in keratinization.
The avian horny layer over the back is composed of a loose network of structurally solid horny cells. This is in contrast to most mammalian epidermal horny cells in which structural keratin is found only in the peripheral cytoplasm, and the interior of the keratinocyte contains soluble products of cytolysis with possibly some free keratin filaments dispersed in the fluid material.
The avian tarsal epidermal horny scales show similarities to both the scales of lizards and snakes and to mammalian tail scales which appear to be homologous structures.
It is suggested that a thin layer of cells containing no detectable disulphide bonds, found in the tarsal scale region of the young chick, is probably mechanically weak and may function as a fission plane for sloughing of the horny layer. A specialized epidermis and thickened horny layer is developed in the fowl on the plantar underside of the toes, but this is quite different in structure from the mammalian plantar epidermis.
The overlapping of zones rich in ribonucleic acid (RNA) and bound cysteine (SH) in the growing feather suggests that protein synthesis and the preparatory stages to keratin disulphide bonding normally occur concurrently in feather formation. This is in contrast to the growing hair which has a region rich in RNA followed immediately before it becomes keratinized by a discrete keratogenous zone weak in RNA but rich in bound cysteine.     

Detecting adherence to the recommended childhood vaccination schedule from user-generated content in a US parenting forum

Vaccine hesitancy is considered as one of the leading causes for the resurgence of vaccine preventable diseases. A non-negligible minority of parents does not fully adhere to the recommended vaccination schedule, leading their children to be partially immunized and at higher risk of contracting vaccine preventable diseases. Here, we leverage more than one million comments of 201,986 users posted from March 2008 to April 2019 on the public online forum BabyCenter US to learn more about such parents. For 32% with geographic location, we find the number of mapped users for each US state resembling the census population distribution with good agreement. We employ Natural Language Processing to identify 6884 and 10,131 users expressing their intention of following the recommended and alternative vaccination schedule, respectively RSUs and ASUs. From the analysis of their activity on the forum we find that ASUs have distinctly different interests and previous experiences with vaccination than RSUs. In particular, ASUs are more likely to follow groups focused on alternative medicine, are two times more likely to have experienced adverse events following immunization, and to mention more serious adverse reactions such as seizure or developmental regression. Content analysis of comments shows that the resources most frequently shared by both groups point to governmental domains (.gov). Finally, network analysis shows that RSUs and ASUs communicate between each other (indicating the absence of echo chambers), however with the latter group being more endogamic and favoring interactions with other ASUs. While our findings are limited to the specific platform analyzed, our approach may provide additional insights for the development of campaigns targeting parents on digital platforms.     

The Critical Periphery in the Growth of Social Protests

Social media have provided instrumental means of communication in many recent political protests. The efficiency of online networks in disseminating timely information has been praised by many commentators; at the same time, users are often derided as “slacktivists” because of the shallow commitment involved in clicking a forwarding button. Here we consider the role of these peripheral online participants, the immense majority of users who surround the small epicenter of protests, representing layers of diminishing online activity around the committed minority. We analyze three datasets tracking protest communication in different languages and political contexts through the social media platform Twitter and employ a network decomposition technique to examine their hierarchical structure. We provide consistent evidence that peripheral participants are critical in increasing the reach of protest messages and generating online content at levels that are comparable to core participants. Although committed minorities may constitute the heart of protest movements, our results suggest that their success in maximizing the number of online citizens exposed to protest messages depends, at least in part, on activating the critical periphery. Peripheral users are less active on a per capita basis, but their power lies in their numbers: their aggregate contribution to the spread of protest messages is comparable in magnitude to that of core participants. An analysis of two other datasets unrelated to mass protests strengthens our interpretation that core-periphery dynamics are characteristically important in the context of collective action events. Theoretical models of diffusion in social networks would benefit from increased attention to the role of peripheral nodes in the propagation of information and behavior.     

Do Emotions Expressed Online Correlate with Actual Changes in Decision-Making?: The Case of Stock Day Traders

Emotions are increasingly inferred linguistically from online data with a goal of predicting off-line behavior. Yet, it is unknown whether emotions inferred linguistically from online communications correlate with actual changes in off-line activity. We analyzed all 886,000 trading decisions and 1,234,822 instant messages of 30 professional day traders over a continuous 2 year period. Linguistically inferring the traders’ emotional states from instant messages, we find that emotions expressed in online communications reflect the same distributions of emotions found in controlled experiments done on traders. Further, we find that expressed online emotions predict the profitability of actual trading behavior. Relative to their baselines, traders who expressed little emotion or traders that expressed high levels of emotion made relatively unprofitable trades. Conversely, traders expressing moderate levels of emotional activation made relatively profitable trades.     

Estimation of Global Network Statistics from Incomplete Data

Complex networks underlie an enormous variety of social, biological, physical, and virtual systems. A profound complication for the science of complex networks is that in most cases, observing all nodes and all network interactions is impossible. Previous work addressing the impacts of partial network data is surprisingly limited, focuses primarily on missing nodes, and suggests that network statistics derived from subsampled data are not suitable estimators for the same network statistics describing the overall network topology. We generate scaling methods to predict true network statistics, including the degree distribution, from only partial knowledge of nodes, links, or weights. Our methods are transparent and do not assume a known generating process for the network, thus enabling prediction of network statistics for a wide variety of applications. We validate analytical results on four simulated network classes and empirical data sets of various sizes. We perform subsampling experiments by varying proportions of sampled data and demonstrate that our scaling methods can provide very good estimates of true network statistics while acknowledging limits. Lastly, we apply our techniques to a set of rich and evolving large-scale social networks, Twitter reply networks. Based on 100 million tweets, we use our scaling techniques to propose a statistical characterization of the Twitter Interactome from September 2008 to November 2008. Our treatment allows us to find support for Dunbar''s hypothesis in detecting an upper threshold for the number of active social contacts that individuals maintain over the course of one week.     

Decrypting Financial Markets through E-Joint Attention Efforts: On-Line Adaptive Networks of Investors in Periods of Market Uncertainty

This paper looks at 800,000 messages on the Unicredit stock, exchanged by 7,500 investors in the Finanzaonline.com forum, between 2005 and 2012 and measured collective interpretations of stock market trends. We examined the correlation patterns between market uncertainty, bad news and investors'' network structure by measuring the investors'' communication patterns. Our results showed that the investors'' network reacted to market trends in different ways: While less turbulent market phases implied less communication, higher market volatility generated more complex communication patterns. While the information content of messages was less technical in situations of uncertainty, bad news caused more informative messages only when market volatility was lower. This meant that bad news had a different impact on network behaviour, depending on market uncertainty. By measuring the investors'' expertise, we found that their behaviour could help predict changes in daily stock returns. We also found that expert investors were more influential in communication processes during high volatility market phases, whereas they had less influence on the real-time forum''s reaction after bad news. Our findings confirm the crucial role of e-communication platforms. However, they also show the need to reconsider the fragility of these collective intelligence systems when under external shocks.     

胶菀属——中国菊科紫菀族的一个新归化属

报道中国东北辽宁省发现的菊科（Asteraceae）紫菀族（Astereae）一个新归化属胶菀属（Grindelia）。它在外形上接近于旋覆花属（1nula）,但区别在于胶菀属花药基部钝,花柱分枝顶端附属物呈披针形或三角形,冠毛鳞片状。依据在中国所采集的标本描述了该属在中国的唯一代表种胶菀（Grindelia squarrosa）的形态特征,并讨论了其自然分布和进入中国的可能途径。     

Molecular phylogeny and evolution of the freshwater eels genus Anguilla based on the whole mitochondrial genome sequences

Molecular phylogenetic analyses were conducted using the whole mitochondrial genome sequences of all 18 species/subspecies of the freshwater eels genus Anguilla to infer their phylogenetic relationships and to evaluate hypotheses about the possible dispersal routes of this genus. The Bayesian and maximum likelihood analyses using a total of 15,187 sites of mitochondrial DNA sequences suggested that A. mossambica was the most basal species of anguillid eel, and that the other species (except for A. borneensis) formed three geographic clades: Atlantic (two species), Oceania (three species), and Indo-Pacific (11 species). The present study clearly indicated a sister relationship between the Atlantic and Oceanian species, which now have distantly separated geographic distributions. This suggests that the previous hypotheses to estimate the dispersal route of anguillid eels into the Atlantic Ocean based on the current geographic distribution of species are unsupported by the present more complete analysis. Alternatively, the unique geographic distribution of the present day species in the genus Anguilla appears to have resulted from multiple dispersal events. Although the age of the beginning of speciation among anguillid eels was tentatively estimated as 20 million years ago using a calibration for bony fishes of 7.3x10(-4) substitutions/site/million years, it is possible that this divergence time was underestimated because of the ecological characteristics of these fishes. The results of the present study suggest that the hypotheses for the dispersal route and divergence time of the genus Anguilla should be reconsidered.     

How to record a million synaptic weights in a hippocampal slice

A key step toward understanding the function of a brain circuit is to find its wiring diagram. New methods for optical stimulation and optical recording of neurons make it possible to map circuit connectivity on a very large scale. However, single synapses produce small responses that are difficult to measure on a large scale. Here I analyze how single synaptic responses may be detectable using relatively coarse readouts such as optical recording of somatic calcium. I model a network consisting of 10,000 input axons and 100 CA1 pyramidal neurons, each represented using 19 compartments with voltage-gated channels and calcium dynamics. As single synaptic inputs cannot produce a measurable somatic calcium response, I stimulate many inputs as a baseline to elicit somatic action potentials leading to a strong calcium signal. I compare statistics of responses with or without a single axonal input riding on this baseline. Through simulations I show that a single additional input shifts the distribution of the number of output action potentials. Stochastic resonance due to probabilistic synaptic release makes this shift easier to detect. With ~80 stimulus repetitions this approach can resolve up to 35% of individual activated synapses even in the presence of 20% recording noise. While the technique is applicable using conventional electrical stimulation and extracellular recording, optical methods promise much greater scaling, since the number of synapses scales as the product of the number of inputs and outputs. I extrapolate from current high-speed optical stimulation and recording methods, and show that this approach may scale up to the order of a million synapses in a single two-hour slice-recording experiment.