Deep Neural Attention for Misinformation and Deception Detection

PhD thesis in Information technologyAt present the influence of social media on society is so much that without it life seems to have no meaning for many. This kind of over-reliance on social media gives an opportunity to the anarchic elements to take undue advantage. Online misinformation and deception are vivid examples of such phenomenon. The misinformation or fake news spreads faster and wider than the true news [32]. The need of the hour is to identify and curb the spread of misinformation and misleading content automatically at the earliest. Several machine learning models have been proposed by the researchers to detect and prevent misinformation and deceptive content. However, these prior works suffer from some limitations: First, they either use feature engineering heavy methods or use intricate deep neural architectures, which are not so transparent in terms of their internal working and decision making. Second, they do not incorporate and learn the available auxiliary and latent cues and patterns, which can be very useful in forming the adequate context for the misinformation. Third, Most of the former methods perform poorly in early detection accuracy measures because of their reliance on features that are usually absent at the initial stage of news or social media posts on social networks. In this dissertation, we propose suitable deep neural attention based solutions to overcome these limitations. For instance, we propose a claim verification model, which learns embddings for the latent aspects such as author and subject of the claim and domain of the external evidence document. This enables the model to learn important additional context other than the textual content. In addition, we also propose an algorithm to extract evidential snippets out of external evidence documents, which serves as explanation of the model’s decisions. Next, we improve this model by using improved claim driven attention mechanism and also generate a topically diverse and non-redundant multi-document fact-checking summary for the claims, which helps to further interpret the model’s decision making. Subsequently, we introduce a novel method to learn influence and affinity relationships among the social media users present on the propagation paths of the news items. By modeling the complex influence relationship among the users, in addition to textual content, we learn the significant patterns pertaining to the diffusion of the news item on social network. The evaluation shows that the proposed model outperforms the other related methods in early detection performance with significant gains. Next, we propose a synthetic headline generation based headline incongruence detection model. Which uses a word-to-word mutual attention based deep semantic matching between original and synthetic news headline to detect incongruence. Further, we investigate and define a new task of incongruence detection in presence of important cardinal values in headline. For this new task, we propose a part-of-speech pattern driven attention based method, which learns requisite context for cardinal values

Sophistication in Service Exports and Economic Growth

Services can now be stored and traded digitally, and they are not subject to many of the trade barriers that physical exports have to overcome. Services are no longer exclusively an input for trade in goods, but have become a “final export” for direct consumption. It is important to note that services not only have become more tradable, but also can be increasingly unbundled: a single service activity in the global supply chain can now be fragmented and done separately at different geographic locations. This has led to a new channel of growth—what we call service export sophistication.Exports, service exports, outsourcing, trade, growth, india, trade barriers, unbundled, supply chain, sophistication, developing countires

Service export sophistication and economic growth

Can increasing sophistication in service exports lead to economic growth? Although services were historically produced primarily for domestic consumption, they are gradually becoming more productive, tradable and unbundled. The authors construct an index of"service exports sophistication"to document this phenomenon. Panel data estimations indicate a positive association between growth in per capita income and higher sophistication of service exports. The results also suggest that this phenomenon is growing in importance over time. Considering the limits of traditional industrialization in igniting global growth, the results provide an alternative channel.Economic Theory&Research,Public Sector Corruption&Anticorruption Measures,Commodities,Housing&Human Habitats,Banks&Banking Reform

Estimation of Enzymatic Activities of Different Species of Mushrooms

Mushrooms are widely spread saprophytic macro-organisms, belong to class fungi growing on dead organic matter of vegetative origin. They can utilize almost all agricultural wastes as their substrates for their growth and metabolism. During the growth of mushroom mycelia and their development into mature fruiting bodies (or sporophores), various biochemical changes are known to occur, as a result of which enzymes are secreted extracellularly to degrade the insoluble materials to simple and soluble molecules. Consequently, enzymes play a significant role in mushroom development; in addition, they also affect the food and nutrient value, flavour and shelf life of these fungi. Pleurotus spp, Volvariella volvaceae and Ganoderma lucidium are edible tropical fast-growing, wood degrading macro fungi that are of economic importance in India as both the sporophores and tuberous sclerotia are not only edible but also are used in medicinal preparations by native doctors. This work was undertaken to evaluate the enzymatic activities of Pleurotus florida, Pleurotus sajor caju, Vovariella volvaceae and Ganoderma lucidium and the effects of these enzymes on shelf life and food nutrients of these mushrooms

Do Farm Programs Explain Mean and Variance of Technical Efficiency? Stochastic Frontier Analysis

Past literature has examined the importance of farm programs on the volatility and returns on general and agriculture economic growth. The objective of this study was to assess the impact of farm program payments on technical efficiency. The study used aggregate state level panel data from the U.S agricultural sector. Results indicate production increasing with increasing units of inputs. Results from this study indicate that farm program payments play an important role in technical efficiency. For example, farm program payments indicate a negative and positive effect on mean and variance of technical efficiency in the long-run and short-run, respectivelyProduction Economics, Productivity Analysis, Risk and Uncertainty,