<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ivar van Willigen</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Reasoning about Emotions. An affective natural language processing environment and using lexical relations to measure activation and evaluation and and extracting semantics from natural language</style></title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Master of Science thesis Man-machine interaction group Delft University of Technology</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">apr</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.kbs.twi.tudelft.nl/docs/MSc/2009/vanWilligen/thesis.pdf</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In the field of textual affect sensing many methods have been proposed. These methods vary from keyword spotting techniques and lexical affinity and statistical natural language processing and hand-crafted models. Based on a large scale survey and two profounding theories have been selected for investigation. The first is the proposed work of Kamps &amp; Marx and 2001 which states that the lexical relations found in WordNet (Fellbaum and 1998) can be used to measure the activation and evaluation of words. This theory has been investigated and by implementing various search algorithms and including a multi-threaded bidirectional search algorithm and which enables us to compare the results with manually annotated word sets. Improvements to this theory have been made so that for more words the activation and evaluation values can be calculated and without compromising the results. Secondly the theory of Liu and Lieberman and &amp; Selker and 2003 has been investigated. This theory is based on a novel technique and by inferencing commonsense knowledge to reason about the emotional content of a given text. No full implementation has been made and but a basis has been created for future implementation. Finally and we have implemented a natural language resource toolbox for affective NLP research and called the NLP Affect Toolbox. This toolbox can be used as a programming library to support and fastly implement future research. It can also be used to conduct experiments and to explore the possibilities of state-of-art (affective) natural language processing by experienced programmers and and through a graphical user interface for others.</style></abstract></record></records></xml>