A proactive intelligent decision support system for predicting the popularity of online news

"Lecture notes in computer science series, ISSN 0302-9743, vol. 9273"

Does VAA popularity pay off ? : Smartvote users preferred candidates and their results in the 2007 Swiss federal elections

Voting is fundamental for democracy, however, this decisive democratic act requires quite an effort. Decision making at elections depends largely on the interest to gather information about candidates and parties, the effort to process the information at hand and the motivation to reach a vote choice. Especially in electoral systems with highly fragmented party systems and hundreds of candidates running for office, the process of decision making in the pre‐election sphere is highly demanding. In the age of information and communication technologies, new possibilities for gathering and processing such information are available. Voting Advice Applications (VAAs) provide guidance to voters prior to the act of voting and assist voters in choosing between different candidates and parties on the basis of issue congruence. Meanwhile widely used all over the world, scientific inquiry into the effect of such tools on electoral behavior is ongoing. This paper adds to the current debate by focusing on whether the popularity of candidates on the Swiss VAA smartvote eventually paid off at the 2007 Swiss federal elections and whether there is a direct link between the performance of a candidate on the tool and his or her electoral performance.

Catalan government popularity. An example of economic effects on sub-national government support

The aim of this essay is to deal with economic voting in contexts ofmultilevel governance and to be a contribution to the debate on attribution of responsibilities in popularity functions literature. We use aggregate and individual data from Catalonia in order to analyse the relation between the state of the economy and the support for a sub-state government. The empirical analysis shows that the responsibility hypothesis works in regional governments without explicit macroeconomic competencies. We have also considered the evaluations of government performance on certain specific policies in order to clarify and determine the factors that drive Catalan government support. The article considers the implications of the findings for future attempts to model party support in a context of the European Union.

Features for mobile applications popularity

Mobile applications market shows one of the highest growth rates for the market of intellectual products. The market is attractive to investors, despite the fact that the major companies of this industry already firmly consolidated its position. Experts predict the growth of the market for mobile applications with the development of mobile technologies in general. To demonstrate the explosive growth of the market and the scale of its impact, it is worth recalling the mobile game Angry Birds, which was able to achieve a huge reach and formed a full-fledged media brand, comparable to the film industry brands. The reasons why some games become popular and others not, are important for understanding the driving factors of the games industry. The Master’s Thesis explores the factors for mobile games applications popularity and ranking and propose recommendations for mobile games app store optimization of app representation. It discovers particular features of mobile games applications and releases’ influence on their popularity. Also the study assumes usage of such business models as The Business Model Canvas by Osterwalder and The Lean Startup Methodology by Ries, and describes the best practices of mobile application development process and market positioning. Moreover, the Master’s Thesis gives examples of multiple case studies about successful mobile apps developers.

Studi di data popularity nell'analisi distribuita su Grid dell'esperimento CMS a LHC

L’esperimento CMS a LHC ha raccolto ingenti moli di dati durante Run-1, e sta sfruttando il periodo di shutdown (LS1) per evolvere il proprio sistema di calcolo. Tra i possibili miglioramenti al sistema, emergono ampi margini di ottimizzazione nell’uso dello storage ai centri di calcolo di livello Tier-2, che rappresentano - in Worldwide LHC Computing Grid (WLCG)- il fulcro delle risorse dedicate all’analisi distribuita su Grid. In questa tesi viene affrontato uno studio della popolarità dei dati di CMS nell’analisi distribuita su Grid ai Tier-2. Obiettivo del lavoro è dotare il sistema di calcolo di CMS di un sistema per valutare sistematicamente l’ammontare di spazio disco scritto ma non acceduto ai centri Tier-2, contribuendo alla costruzione di un sistema evoluto di data management dinamico che sappia adattarsi elasticamente alle diversi condizioni operative - rimuovendo repliche dei dati non necessarie o aggiungendo repliche dei dati più “popolari” - e dunque, in ultima analisi, che possa aumentare l’“analysis throughput” complessivo. Il Capitolo 1 fornisce una panoramica dell’esperimento CMS a LHC. Il Capitolo 2 descrive il CMS Computing Model nelle sue generalità, focalizzando la sua attenzione principalmente sul data management e sulle infrastrutture ad esso connesse. Il Capitolo 3 descrive il CMS Popularity Service, fornendo una visione d’insieme sui servizi di data popularity già presenti in CMS prima dell’inizio di questo lavoro. Il Capitolo 4 descrive l’architettura del toolkit sviluppato per questa tesi, ponendo le basi per il Capitolo successivo. Il Capitolo 5 presenta e discute gli studi di data popularity condotti sui dati raccolti attraverso l’infrastruttura precedentemente sviluppata. L’appendice A raccoglie due esempi di codice creato per gestire il toolkit attra- verso cui si raccolgono ed elaborano i dati.

Predicting CMS datasets popularity with machine learning

In CMS è stato lanciato un progetto di Data Analytics e, all’interno di esso, un’attività specifica pilota che mira a sfruttare tecniche di Machine Learning per predire la popolarità dei dataset di CMS. Si tratta di un’osservabile molto delicata, la cui eventuale predizione premetterebbe a CMS di costruire modelli di data placement più intelligenti, ampie ottimizzazioni nell’uso dello storage a tutti i livelli Tiers, e formerebbe la base per l’introduzione di un solito sistema di data management dinamico e adattivo. Questa tesi descrive il lavoro fatto sfruttando un nuovo prototipo pilota chiamato DCAFPilot, interamente scritto in python, per affrontare questa sfida.

Breast cancer on the world wide web: cross sectional survey of quality of information and popularity of websites.

OBJECTIVES: To determine the characteristics of popular breast cancer related websites and whether more popular sites are of higher quality. DESIGN: The search engine Google was used to generate a list of websites about breast cancer. Google ranks search results by measures of link popularity---the number of links to a site from other sites. The top 200 sites returned in response to the query "breast cancer" were divided into "more popular" and "less popular" subgroups by three different measures of link popularity: Google rank and number of links reported independently by Google and by AltaVista (another search engine). MAIN OUTCOME MEASURES: Type and quality of content. RESULTS: More popular sites according to Google rank were more likely than less popular ones to contain information on ongoing clinical trials (27% v 12%, P=0.01 ), results of trials (12% v 3%, P=0.02), and opportunities for psychosocial adjustment (48% v 23%, P<0.01). These characteristics were also associated with higher number of links as reported by Google and AltaVista. More popular sites by number of linking sites were also more likely to provide updates on other breast cancer research, information on legislation and advocacy, and a message board service. Measures of quality such as display of authorship, attribution or references, currency of information, and disclosure did not differ between groups. CONCLUSIONS: Popularity of websites is associated with type rather than quality of content. Sites that include content correlated with popularity may best meet the public's desire for information about breast cancer.

PARENT-CHILD RELATIONSHIP QUALITY AND THE INFLUENCE ON SOCIOMETRIC VERSUS PEER-PERCEIVED POPULARITY

The purpose of this study was to compare factors in the parent-child relationships of peer perceived popular adolescents to those of sociometrically popular adolescents. Factors included autonomy, relatedness, and idealization. Participants were 71 8th grade adolescents. Results showed similarities in parent-child relationships between perceived popular and sociometrically popular adolescents for autonomy, relatedness, and idealization. Results suggest that future research should explore other factors, such as affection from mother and father and levels of psychological control behavior to differentiate perceived popularity from sociometrically popular adolescents.

Popularity based distribution schemes for P2P assisted streaming of VoD contents

The Video on Demand (VoD) service is becoming a dominant service in the telecommunication market due to the great convenience regarding the choice of content items and their independent viewing time. However, it comes with the downsides of high server storage and capacity demands because of the large variety of content items and the high amount of traffic generated for serving all requests. Storing part of the popular contents on the peers brings certain advantages but, it still has issues regarding the overall traffic in the core of the network and the scalability. Therefore, we propose a P2P assisted model for streaming VoD contents that takes advantage of the clients unused uplink and storage capacity to serve requests of other clients and we present popularity based schemes for distribution of both the popular and unpopular contents on the peers. The proposed model and the schemes prove to reduce the streaming traffic in the core of the network, improve the responsiveness of the system and increase its scalability.

P2P assisted streaming for low popularity VoD contents

The Video on Demand (VoD) service is becoming a dominant service in the telecommunication market due to the great convenience regarding the choice of content items and their independent viewing time. However, due to its high traffic demand nature, the VoD streaming systems are faced with the problem of huge amounts of traffic generated in the core of the network, especially for serving the requests for content items that are not in the top popularity range. Therefore, we propose a peer assisted VoD model that takes advantage of the clients unused uplink and storage capacity to serve requests for less popular items with the objective to keep the traffic on the periphery of the network, reduce the transport cost in the core of the network and make the system more scalable.

The Influence of Gender, Intellectual Ability, Academic Self-Concept, Self-Regulation, Learning Strategies, Popularity and Parent Involvement in Early Adolescence

The present study examined the predictive effects of gender, intellectual ability, self-concept, motivation, learning strategies, popularity and parent involvement on academic achievement. Hiearchical regression analysis were performed with six steps in which each variable was included, among a sample of 1398 high school students (mean age = 12.5; standard deviation = .67) of eight education centers from the province of Alicante (Spain). The results revealed significant predictive effects of all of the variables, explaining 59.1% of the total variance.