This short paper describes a sentiment analysis system for micro-post data that includes analysis of tweets from Twitter and Short Messaging Service (SMS) text messages. We discuss our system that makes use of Word Sense Disambiguation techniques in sentiment analysis at the message level, where the entire tweet or SMS text was analysed to determine its dominant sentiment. Previous work done in the area of Word Sense Disambiguation does not throw light on its influence on the analysis of social-media text and micropost data, which is what our work aims to achieve. Our experiments show that the use of Word Sense Disambiguation alone has resulted in an improved sentiment analysis system that outperforms systems built without incorporating Word Sense Disambiguation.
In a variety of problem domains, it has been observed that the aggregate opinions of groups are often more accurate than those of the constituent individuals, a phenomenon that has been dubbed the “wisdom of the crowd”. However, due to the varying contexts, sample sizes, methodologies, and scope of previous studies, it has been difficult to gauge the extent to which conclusions generalize. To investigate this question, we carried out a large online experiment to systematically evaluate crowd performance on 1,000 questions across 50 topical domains. We further tested the effect of different types of social influence on crowd performance. For example, in one condition, participants could see the cumulative crowd answer before providing their own. In total, we collected more than 500,000 responses from nearly 2,000 participants. We have three main results. First, averaged across all questions, we find that the crowd indeed performs better than the average individual in the crowd—but we also find substantial heterogeneity in performance across questions. Second, we find that crowd performance is generally more consistent than that of individuals; as a result, the crowd does considerably better than individuals when performance is computed on a full set of questions within a domain. Finally, we find that social influence can, in some instances, lead to herding, decreasing crowd performance. Our findings illustrate some of the subtleties of the wisdom-of-crowds phenomenon, and provide insights for the design of social recommendation platforms.
The rapid growth of the construction industry has led to an increased demand for building materials, particularly aggregates. The extraction of natural aggregates has significant environmental impacts, including landscape alteration and depletion of natural resources. Therefore, finding alternative materials for sustainable construction is essential. This project aims to investigate the potential utilization of ceramic tile waste as a partial replacement for fine aggregate in cement mortar. The research methodology involves collecting ceramic tile waste from local sources and conducting laboratory experiments to evaluate the physical and mechanical properties of cement mortar incorporating different percentages of ceramic tile waste. The properties investigated include workability, compressive strength, flexural strength, and water absorption capacity. The experimental results demonstrate that the addition of ceramic tile waste as a partial replacement for fine aggregate in cement mortar exhibits promising outcomes. The workability of the mortar is within an acceptable range for construction purposes, and the compressive and flexural strengths show satisfactory performance. Moreover, the water absorption capacity of the mortar reduces with an increase in the percentage of ceramic tile waste, indicating improved durability. This research contributes to the sustainable utilization of ceramic tile waste, reducing the environmental burden associated with waste disposal and conserving natural resources. The findings provide valuable insights into the feasibility of incorporating ceramic tile waste in cement mortar, potentially leading to the development of cost-effective and environmentally friendly construction materials
Solo sign-on (SSO) is a new authentication mechanism that enables a legal user with a single credential to be authenticated by multiple service providers in a distributed computer network. Recently, a SSO scheme proposed and claimed its security by providing well organized security arguments. But their scheme is actually insecure as it fails to meet credential privacy and soundness of authentication. Specifically, we present two impersonation attacks i.e., credential recovering attack and impersonation attack without credentials. So we propose a more authentication scheme that overcomes these attacks and flaws by make use of efficient verifiable encryption of RSA signatures. We promote the formal study of the soundness of authentication as one open problem.
Traditionally a communication channel is mandatory for performing verbal and written communication. The same use case when mapped to information and communication technology gives rise to one of the concept called textual communication, which deals with transmitting text using a communication channel. Every symbol used in the text needs a unit of storage called byte, the metric for transmission and storage resources. Due to the limitations of the transmission channel with respect to bandwidth and storage with respect to size, considerable models, methods and technologies have been proposed and evolved to optimally utilize the said resources without compromising the content and the semantics of the text. This work carried out proposes a novel framework for representing and storing textual data called Ordell Ugo Nano hereinafter termed as OUNano, which can be seamlessly integrated with existing communication and storage infrastructure. The proposed methodology attempts to best optimize the utilization of existing digital storage and communication resources, thus allowing such resources to be exploited to their maximum potential. This facilitates a considerably higher rate of textual data transmission and processing in communication channels, along with significant increase in storage capacities of the existing storage assets in place, without investing in additional resources.
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