Sequential processing deficits of reading disabled persons is independent of inter-stimulus interval

AbstractDevelopmental dyslexia is a language-based learning disability with frequently associated non-linguistic sensory deficits that have been the basis of various perception-based theories. It remains an open question whether the underlying deficit in dyslexia is a low level impairment that causes speech and orthographic perception deficits that in turn impedes higher phonological and reading processes, or a high level impairment that affects both perceptual and reading related skills.We investigated by means of contrast detection thresholds two low-level theories of developmental dyslexia, the magnocellular and the fast temporal processing hypotheses, as well as a more recent suggestion that dyslexics have difficulties in sequential comparison tasks that can be attributed to a higher-order deficit. It was found that dyslexics had significantly higher thresholds only on a sequential, but not a spatial, detection task, and that this impairment was found to be independent of the inter-stimulus interval. We also found that the poor performance of dyslexics on the temporal task was dependent on the size of the required memory trace of the image rather than on the number of images. Our findings do not support the magnocellular theory and challenge the fast temporal deficit hypothesis. We suggest that dyslexics may have a higher order, dual mechanism impairment. We also discuss the clinical implications of our findings

Predicting Rising Follower Counts on Twitter Using Profile Information

When evaluating the cause of one's popularity on Twitter, one thing is considered to be the main driver: Many tweets. There is debate about the kind of tweet one should publish, but little beyond tweets. Of particular interest is the information provided by each Twitter user's profile page. One of the features are the given names on those profiles. Studies on psychology and economics identified correlations of the first name to, e.g., one's school marks or chances of getting a job interview in the US. Therefore, we are interested in the influence of those profile information on the follower count. We addressed this question by analyzing the profiles of about 6 Million Twitter users. All profiles are separated into three groups: Users that have a first name, English words, or neither of both in their name field. The assumption is that names and words influence the discoverability of a user and subsequently his/her follower count. We propose a classifier that labels users who will increase their follower count within a month by applying different models based on the user's group. The classifiers are evaluated with the area under the receiver operator curve score and achieves a score above 0.800.Comment: 10 pages, 3 figures, 8 tables, WebSci '17, June 25--28, 2017, Troy, NY, US

String Indexing for Patterns with Wildcards

We consider the problem of indexing a string $t$ of length $n$ to report the occurrences of a query pattern $p$ containing $m$ characters and $j$ wildcards. Let $occ$ be the number of occurrences of $p$ in $t$, and $\sigma$ the size of the alphabet. We obtain the following results. - A linear space index with query time $O(m+\sigma^j \log \log n + occ)$. This significantly improves the previously best known linear space index by Lam et al. [ISAAC 2007], which requires query time $\Theta(jn)$ in the worst case. - An index with query time $O(m+j+occ)$ using space $O(\sigma^{k^2} n \log^k \log n)$, where $k$ is the maximum number of wildcards allowed in the pattern. This is the first non-trivial bound with this query time. - A time-space trade-off, generalizing the index by Cole et al. [STOC 2004]. We also show that these indexes can be generalized to allow variable length gaps in the pattern. Our results are obtained using a novel combination of well-known and new techniques, which could be of independent interest

Competition and Selection Among Conventions

In many domains, a latent competition among different conventions determines which one will come to dominate. One sees such effects in the success of community jargon, of competing frames in political rhetoric, or of terminology in technical contexts. These effects have become widespread in the online domain, where the data offers the potential to study competition among conventions at a fine-grained level. In analyzing the dynamics of conventions over time, however, even with detailed on-line data, one encounters two significant challenges. First, as conventions evolve, the underlying substance of their meaning tends to change as well; and such substantive changes confound investigations of social effects. Second, the selection of a convention takes place through the complex interactions of individuals within a community, and contention between the users of competing conventions plays a key role in the convention's evolution. Any analysis must take place in the presence of these two issues. In this work we study a setting in which we can cleanly track the competition among conventions. Our analysis is based on the spread of low-level authoring conventions in the eprint arXiv over 24 years: by tracking the spread of macros and other author-defined conventions, we are able to study conventions that vary even as the underlying meaning remains constant. We find that the interaction among co-authors over time plays a crucial role in the selection of them; the distinction between more and less experienced members of the community, and the distinction between conventions with visible versus invisible effects, are both central to the underlying processes. Through our analysis we make predictions at the population level about the ultimate success of different synonymous conventions over time--and at the individual level about the outcome of "fights" between people over convention choices.Comment: To appear in Proceedings of WWW 2017, data at https://github.com/CornellNLP/Macro

On the Origins of Memes by Means of Fringe Web Communities

Internet memes are increasingly used to sway and manipulate public opinion. This prompts the need to study their propagation, evolution, and influence across the Web. In this paper, we detect and measure the propagation of memes across multiple Web communities, using a processing pipeline based on perceptual hashing and clustering techniques, and a dataset of 160M images from 2.6B posts gathered from Twitter, Reddit, 4chan's Politically Incorrect board (/pol/), and Gab, over the course of 13 months. We group the images posted on fringe Web communities (/pol/, Gab, and The_Donald subreddit) into clusters, annotate them using meme metadata obtained from Know Your Meme, and also map images from mainstream communities (Twitter and Reddit) to the clusters. Our analysis provides an assessment of the popularity and diversity of memes in the context of each community, showing, e.g., that racist memes are extremely common in fringe Web communities. We also find a substantial number of politics-related memes on both mainstream and fringe Web communities, supporting media reports that memes might be used to enhance or harm politicians. Finally, we use Hawkes processes to model the interplay between Web communities and quantify their reciprocal influence, finding that /pol/ substantially influences the meme ecosystem with the number of memes it produces, while \td has a higher success rate in pushing them to other communities.Comment: A shorter version of this paper appears in the Proceedings of 18th ACM Internet Measurement Conference (IMC 2018). This is the full versio

Modeling the efficient access of full-text information

The title of this paper describes a research goal set by many offices within US DOE. This paper reviews efficient full-text searching techniques being developed to better understand and meet this goal. Classical computer human interaction (CHI) approaches provided by commercial information retrieval (IR) engines fail to contextualize information in ways that facilitate timely decision making. Use of advanced CHI techniques (eg, visualization) in combination with deductive database technology augment the weaknesses found in presentation capabilities of IR engines and are discussed. Various techniques employed in a Web-based prototype system currently under development are presented

Determination of alpha_s using Jet Rates at LEP with the OPAL detector

Hadronic events produced in e+e- collisions by the LEP collider and recorded by the OPAL detector were used to form distributions based on the number of reconstructed jets. The data were collected between 1995 and 2000 and correspond to energies of 91 GeV, 130-136 GeV and 161-209 GeV. The jet rates were determined using four different jet-finding algorithms (Cone, JADE, Durham and Cambridge). The differential two-jet rate and the average jet rate with the Durham and Cambridge algorithms were used to measure alpha(s) in the LEP energy range by fitting an expression in which order alpah_2s calculations were matched to a NLLA prediction and fitted to the data. Combining the measurements at different centre-of-mass energies, the value of alpha_s (Mz) was determined to be alpha(s)(Mz)=0.1177+-0.0006(stat.)+-0.0012$(expt.)+-0.0010(had.)+-0.0032(theo.) \.Comment: 40 pages, 17 figures, Submitted to Euro. Phys. J.

Colour reconnection in e+e- -> W+W- at sqrt(s) = 189 - 209 GeV

The effects of the final state interaction phenomenon known as colour reconnection are investigated at centre-of-mass energies in the range sqrt(s) ~ 189-209 GeV using the OPAL detector at LEP. Colour reconnection is expected to affect observables based on charged particles in hadronic decays of W+W-. Measurements of inclusive charged particle multiplicities, and of their angular distribution with respect to the four jet axes of the events, are used to test models of colour reconnection. The data are found to exclude extreme scenarios of the Sjostrand-Khoze Type I (SK-I) model and are compatible with other models, both with and without colour reconnection effects. In the context of the SK-I model, the best agreement with data is obtained for a reconnection probability of 37%. Assuming no colour reconnection, the charged particle multiplicity in hadronically decaying W bosons is measured to be (nqqch) = 19.38+-0.05(stat.)+-0.08 (syst.).Comment: 30 pages, 9 figures, Submitted to Euro. Phys. J.

Measurements of Flavour Dependent Fragmentation Functions in Z^0 -> qq(bar) Events

Fragmentation functions for charged particles in Z -> qq(bar) events have been measured for bottom (b), charm (c) and light (uds) quarks as well as for all flavours together. The results are based on data recorded between 1990 and 1995 using the OPAL detector at LEP. Event samples with different flavour compositions were formed using reconstructed D* mesons and secondary vertices. The \xi_p = ln(1/x_E) distributions and the position of their maxima \xi_max are also presented separately for uds, c and b quark events. The fragmentation function for b quarks is significantly softer than for uds quarks.Comment: 29 pages, LaTeX, 5 eps figures (and colour figs) included, submitted to Eur. Phys. J.