Sentiment Analysis and Stance Detection on German YouTube Comments on Gender Diversity

[EN] This paper explores different options of detecting the stance of German YouTube comments regarding the topic of gender diversity and compares the respective results with those of sentiment analysis, showing that these are two very different NLP tasks focusing on distinct characteristics of the discourse. While an already existing model was used to analyze the comments sentiment (BERT), the comments stance was first annotated and then used to train different models SVM with TF-IDF, DistilBERT, LSTM and CNN for predicting the stance of unseen comments. The best results were achieved by the CNN, reaching 78.3% accuracy (92% after dataset normalization) on the test set. Whereas the most common stance identified in the comments is a neutral one (neither completely in favor nor completely against gender diversity), the overall sentiment of the discourse turns out to be negative. This shows that the discourse revolving around the topic of gender diversity in YouTube comments is filled with strong opinions, on the one hand, but also opens up a space for anonymously inquiring and learning about the topic and its implications, on the other. Our research thereby (1) contributes to the understanding and application of different NLP tasks used to predict the sentiment and stance of unstructured textual data, and (2) provides relevant insights into society s attitudes towards a changing system of values and beliefs.Melnyk, L.; Feld, L. (2022). Sentiment Analysis and Stance Detection on German YouTube Comments on Gender Diversity. Journal of Computer-Assisted Linguistic Research. 6:59-86. https://doi.org/10.4995/jclr.2022.182245986

Cloud Computing and Grid Computing 360-Degree Compared

Cloud Computing has become another buzzword after Web 2.0. However, there are dozens of different definitions for Cloud Computing and there seems to be no consensus on what a Cloud is. On the other hand, Cloud Computing is not a completely new concept; it has intricate connection to the relatively new but thirteen-year established Grid Computing paradigm, and other relevant technologies such as utility computing, cluster computing, and distributed systems in general. This paper strives to compare and contrast Cloud Computing with Grid Computing from various angles and give insights into the essential characteristics of both.Comment: IEEE Grid Computing Environments (GCE08) 200

Cross-layer Peer-to-Peer Computing in Mobile Ad Hoc Networks

The future information society is expected to rely heavily on wireless technology. Mobile access to the Internet is steadily gaining ground, and could easily end up exceeding the number of connections from the fixed infrastructure. Picking just one example, ad hoc networking is a new paradigm of wireless communication for mobile devices. Initially, ad hoc networking targeted at military applications as well as stretching the access to the Internet beyond one wireless hop. As a matter of fact, it is now expected to be employed in a variety of civilian applications. For this reason, the issue of how to make these systems working efficiently keeps the ad hoc research community active on topics ranging from wireless technologies to networking and application systems. In contrast to traditional wire-line and wireless networks, ad hoc networks are expected to operate in an environment in which some or all the nodes are mobile, and might suddenly disappear from, or show up in, the network. The lack of any centralized point, leads to the necessity of distributing application services and responsibilities to all available nodes in the network, making the task of developing and deploying application a hard task, and highlighting the necessity of suitable middleware platforms. This thesis studies the properties and performance of peer-to-peer overlay management algorithms, employing them as communication layers in data sharing oriented middleware platforms. The work primarily develops from the observation that efficient overlays have to be aware of the physical network topology, in order to reduce (or avoid) negative impacts of application layer traffic on the network functioning. We argue that cross-layer cooperation between overlay management algorithms and the underlying layer-3 status and protocols, represents a viable alternative to engineer effective decentralized communication layers, or eventually re-engineer existing ones to foster the interconnection of ad hoc networks with Internet infrastructures. The presented approach is twofold. Firstly, we present an innovative network stack component that supports, at an OS level, the realization of cross-layer protocol interactions. Secondly, we exploit cross-layering to optimize overlay management algorithms in unstructured, structured, and publish/subscribe platforms

Engineering Self-Adaptive Collective Processes for Cyber-Physical Ecosystems

The pervasiveness of computing and networking is creating significant opportunities for building valuable socio-technical systems. However, the scale, density, heterogeneity, interdependence, and QoS constraints of many target systems pose severe operational and engineering challenges. Beyond individual smart devices, cyber-physical collectives can provide services or solve complex problems by leveraging a “system effect” while coordinating and adapting to context or environment change. Understanding and building systems exhibiting collective intelligence and autonomic capabilities represent a prominent research goal, partly covered, e.g., by the field of collective adaptive systems. Therefore, drawing inspiration from and building on the long-time research activity on coordination, multi-agent systems, autonomic/self-* systems, spatial computing, and especially on the recent aggregate computing paradigm, this thesis investigates concepts, methods, and tools for the engineering of possibly large-scale, heterogeneous ensembles of situated components that should be able to operate, adapt and self-organise in a decentralised fashion. The primary contribution of this thesis consists of four main parts. First, we define and implement an aggregate programming language (ScaFi), internal to the mainstream Scala programming language, for describing collective adaptive behaviour, based on field calculi. Second, we conceive of a “dynamic collective computation” abstraction, also called aggregate process, formalised by an extension to the field calculus, and implemented in ScaFi. Third, we characterise and provide a proof-of-concept implementation of a middleware for aggregate computing that enables the development of aggregate systems according to multiple architectural styles. Fourth, we apply and evaluate aggregate computing techniques to edge computing scenarios, and characterise a design pattern, called Self-organising Coordination Regions (SCR), that supports adjustable, decentralised decision-making and activity in dynamic environments.Con lo sviluppo di informatica e intelligenza artificiale, la diffusione pervasiva di device computazionali e la crescente interconnessione tra elementi fisici e digitali, emergono innumerevoli opportunità per la costruzione di sistemi socio-tecnici di nuova generazione. Tuttavia, l'ingegneria di tali sistemi presenta notevoli sfide, data la loro complessità—si pensi ai livelli, scale, eterogeneità, e interdipendenze coinvolti. Oltre a dispositivi smart individuali, collettivi cyber-fisici possono fornire servizi o risolvere problemi complessi con un “effetto sistema” che emerge dalla coordinazione e l'adattamento di componenti fra loro, l'ambiente e il contesto. Comprendere e costruire sistemi in grado di esibire intelligenza collettiva e capacità autonomiche è un importante problema di ricerca studiato, ad esempio, nel campo dei sistemi collettivi adattativi. Perciò, traendo ispirazione e partendo dall'attività di ricerca su coordinazione, sistemi multiagente e self-*, modelli di computazione spazio-temporali e, specialmente, sul recente paradigma di programmazione aggregata, questa tesi tratta concetti, metodi, e strumenti per l'ingegneria di ensemble di elementi situati eterogenei che devono essere in grado di lavorare, adattarsi, e auto-organizzarsi in modo decentralizzato. Il contributo di questa tesi consiste in quattro parti principali. In primo luogo, viene definito e implementato un linguaggio di programmazione aggregata (ScaFi), interno al linguaggio Scala, per descrivere comportamenti collettivi e adattativi secondo l'approccio dei campi computazionali. In secondo luogo, si propone e caratterizza l'astrazione di processo aggregato per rappresentare computazioni collettive dinamiche concorrenti, formalizzata come estensione al field calculus e implementata in ScaFi. Inoltre, si analizza e implementa un prototipo di middleware per sistemi aggregati, in grado di supportare più stili architetturali. Infine, si applicano e valutano tecniche di programmazione aggregata in scenari di edge computing, e si propone un pattern, Self-Organising Coordination Regions, per supportare, in modo decentralizzato, attività decisionali e di regolazione in ambienti dinamici

Support for adaptivity in ARMCI using migratable objects

Many new paradigms of parallel programming have emerged that compete with and complement the standard and well-established MPI model. Most notable, and suc-cessful, among these are models that support some form of global address space. At the same time, approaches based on migratable objects (also called virtualized processes) have shown that resource management concerns can be sep-arated effectively from the overall parallel programming ef-fort. For example, Charm++ supports dynamic load bal-ancing via an intelligent adaptive run-time system. It is also becoming clear that a multi-paradigm approach that allows modules written in one or more paradigms to coexist and co-operate will be necessary to tame the parallel pro-gramming challenge. ARMCI is a remote memory copy library that serves as a foundation of many global address space languages and libraries. This paper presents our preliminary work on inte-grating and supporting ARMCI with the adaptive run-time system of Charm++ as a part of our overall effort in the multi-paradigm approach.

Viper : a visualisation tool for parallel program construction

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Orchestrating the Dynamic Adaptation of Distributed Software with Process Technology

Software systems are becoming increasingly complex to develop, understand, analyze, validate, deploy, configure, manage and maintain. Much of that complexity is related to ensuring adequate quality levels to services provided by software systems after they are deployed in the field, in particular when those systems are built from and operated as a mix of proprietary and non-proprietary components. That translates to increasing costs and difficulties when trying to operate large-scale distributed software ensembles in a way that continuously guarantees satisfactory levels of service. A solution can be to exert some form of dynamic adaptation upon running software systems: dynamic adaptation can be defined as a set of automated and coordinated actions that aim at modifying the structure, behavior and performance of a target software system, at run time and without service interruption, typically in response to the occurrence of some condition(s). To achieve dynamic adaptation upon a given target software system, a set of capabilities, including monitoring, diagnostics, decision, actuation and coordination, must be put in place. This research addresses the automation of decision and coordination in the context of an end-to-end and externalized approach to dynamic adaptation, which allows to address as its targets legacy and component-based systems, as well as new systems developed from scratch. In this approach, adaptation provisions are superimposed by a separate software platform, which operates from the outside of and orthogonally to the target application as a whole; furthermore, a single adaptation possibly spans concerted interventions on a multiplicity of target components. To properly orchestrate those interventions, decentralized process technology is employed for describing, activating and coordinating the work of a cohort of software actuators, towards the intended end-to-end dynamic adaptation. The approach outlined above, has been implemented in a prototype, code-named Workflakes, within the Kinesthetics eXtreme project investigating externalized dynamic adaptation, carried out by the Programming Systems Laboratory of Columbia University, and has been employed in a set of diverse case studies. This dissertation discusses and evaluates the concept of process-based orchestration of dynamic adaptation and the Workflakes prototype on the basis of the results of those case studies