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The capacity of communities to reduce negative impacts of climate change on their lives and livelihoods is a function of socio-economic conditions, infrastructure, government accountability and institutional responsiveness and not the least social capital. Africa’s most densely populated region, the Lake Victoria basin (LVB), home to over 30 million people, is one example of a likely future climat

Important factors behind high levels of vulnerability and low adaptive capacity to climate variability and change in the developing world are direct reliance on natural resources, poverty and limited abilities to adapt financially and institutionally. In this study, focusing on the Lake Victoria Basin, a multitude of stressors on livelihoods, including climate related factors, are faced by the rur

This paper examines two failed land acquisition processes for food and biofuels production in Africa with the aim to establishing more equitable governance strategies. More specifically it explores the roles of certification schemes and codes-of-conduct can play in these processes. The two cases used are the South Korean Daewoo Logistics case in Madagascar and the Swedish SEKAB in Tanzania. The me

In this article, we address the problem of automatic age estimation of web users based on their posts. Most studies on age identification treat the issue as a classification problem. Instead of following an age category classification approach, we investigate the appropriateness of several regression algorithms on the task of age estimation. We evaluate a number of well-known and widely used machi

In the present article, we address the problem of automatic gender classification of web blog authors. More specifically, we employ eight widely used machine learning algorithms, in order to study the effectiveness of feature selection on improving the accuracy of gender classification. The feature ranking is performed over a set of statistical, part-of-speech tagging and language model features.

In this article we present a methodology for classification of text from web authors, using sociolinguistic inspired text features. The proposed methodology uses a baseline text mining based feature set, which is combined with text features that quantify results from theoretical and sociolinguistic studies. Two combination approaches were evaluated and the evaluation results indicated a significan

In this paper, we report on a preliminary study we carried out for identifying patterns that characterize the genre type of Greek texts. In the course of our study, we address four distinct genre types, we record their observable stylistic elements and we indicate their exploitation for automatic genre-based document classi-fication. The findings of our study demonstrate that texts contain lexical

The automatic detection of seven types of modifiers was studied: Certainty, Uncertainty, Hypotheticality, Prediction, Recommendation, Concession/Contrast and Source. A classifier aimed at detecting local cue words that signal the categories was the most successful method for five of the categories. For Prediction and Hypotheticality, however, better results were obtained with a classifier trained

The problem of identifying and correctly attributing speaker stance in human communication is addressed in this paper. The data set consists of political blogs dealing with the 2016 British referendum. A cognitive-functional framework is adopted with data annotated for six notional stance categories: concession/contrariness, hypotheticality, need/ requirement, prediction, source of knowledge, and