New topic detection in microblogs and topic model evaluation using topical alignment

textThis thesis deals with topic model evaluation and new topic detection in microblogs. Microblogs are short and thus may not carry any contextual clues. Hence it becomes challenging to apply traditional natural language processing algorithms on such data. Graphical models have been traditionally used for topic discovery and text clustering on sets of text-based documents. Their unsupervised nature allows topic models to be trained easily on datasets meant for specific domains. However the advantage of not requiring annotated data comes with a drawback with respect to evaluation difficulties. The problem aggravates when the data comprises microblogs which are unstructured and noisy. We demonstrate the application of three types of such models to microblogs - the Latent Dirichlet Allocation, the Author-Topic and the Author-Recipient-Topic model. We extensively evaluate these models under different settings, and our results show that the Author-Recipient-Topic model extracts the most coherent topics. We also addressed the problem of topic modeling on short text by using clustering techniques. This technique helps in boosting the performance of our models. Topical alignment is used for large scale assessment of topical relevance by comparing topics to manually generated domain specific concepts. In this thesis we use this idea to evaluate topic models by measuring misalignments between topics. Our study on comparing topic models reveals interesting traits about Twitter messages, users and their interactions and establishes that joint modeling on author-recipient pairs and on the content of tweet leads to qualitatively better topic discovery. This thesis gives a new direction to the well known problem of topic discovery in microblogs. Trend prediction or topic discovery for microblogs is an extensive research area. We propose the idea of using topical alignment to detect new topics by comparing topics from the current week to those of the previous week. We measure correspondence between a set of topics from the current week and a set of topics from the previous week to quantify five types of misalignments: \textit{junk, fused, missing} and \textit{repeated}. Our analysis compares three types of topic models under different settings and demonstrates how our framework can detect new topics from topical misalignments. In particular so-called \textit{junk} topics are more likely to be new topics and the \textit{missing} topics are likely to have died or die out. To get more insights into the nature of microblogs we apply topical alignment to hashtags. Comparing topics to hashtags enables us to make interesting inferences about Twitter messages and their content. Our study revealed that although a very small proportion of Twitter messages explicitly contain hashtags, the proportion of tweets that discuss topics related to hashtags is much higher.Computer Science

Impact of control measures in fisheries management: evidence from Bangladesh's industrial trawl fishery

This paper examines the effectiveness of different management tools, particularly input and quality controls on Bangladesh's industrial trawl fishery using Stochastic Frontier Analysis (SFA). Results show that the efficiency of the industrial trawl fishery comes from multiple owner managed vessels, export oriented vessels and registered vessels that are mainly engaged in double rigger trawling. Results also indicate that freezer vessels with small storage capacity, using small gear, are relatively less efficient. This study also shows that over the period shrimp vessels are technically more efficient than fish vessels.Industrial trawl fishery, input and quality control, efficiency, Bangladesh

Distortions to Agricultural Incentives in Bangladesh

Distorted incentives, agricultural and trade policy reforms, national agricultural development, Agricultural and Food Policy, International Relations/Trade, F13, F14, Q17, Q18,

To Connect is to Be Influenced: What Determines a Third-party’s Forgiveness Attitudes to Conflicting Groups’ Violent Partisan Members

The present research sought to answer the question of what determines an uninvolved third party’s forgiveness attitudes to conflicting groups’ violent partisan members. Specifically, Bangladeshi participants read a fictitious interview with a radicalized Palestinian who declared his intention to avenge himself against Israelis for his personal and collective plight by carrying out a suicide bombing attack. Findings revealed that an empathy manipulation (high empathy = other focused or low empathy = objective focused) influenced participants’ forgiveness attitudes towards the radicalized Palestinian such that in the high empathy condition participants were more forgiving of the target than participants in the low empathy condition. Moreover, while the strength of their religious identification (Islam) played no significant role, participants’ tendency to attribute the target’s decision to situational factors fully mediated the effects of empathy on forgiveness

緑膿菌と大腸菌由来のCoA,ATP非依存N-ミリストイル化酵素によるアシル化ペプチドの合成と分解

博士(工学)大阪市立大

Women mobilizing: new forms and challenges

Star Magazine: Special feature- International Women's Da

Investigation of Physicochemical Properties of PVA-GANT Mucoadhesive Hydrogels

The aim of this work was the manufacture and characterisation of novel chemically cross-linked mucoadhesive PVA-GANT hydrogels prepared by using autoclaving. Particularly, the study was focused on the physicochemical and pharmaceutical properties of these hydrogels with regards to potential applications for drug delivery and wound dressing. PVA-GANT hydrogels with different molar ratios and total concentrations of polymers in solution were prepared using a standard sterilisation autoclave. The physico-chemical properties were characterised by various techniques including IR spectroscopy, Texture Analysis and SEM and thermo-analytical techniques (DSC and TGA). Pharmaceutical characteristics were obtained in drug loading/release tests and microbiological assays. The results have shown that the properties of hydrogels (swelling degree, mechanical properties, internal structure, drug loading/release and antimicrobial properties) are very dependent on the polymer composition