title: Acquiring and Exploiting Lexical Knowledge for Twitter Sentiment Analysis

authors: Bravo-Marquez, Felipe

subjects: sentiment analysis

abstract: The most popular sentiment analysis task in Twitter is the automatic classification of tweets into sentiment categories such as positive, negative, and neutral. State-of-the-art solutions to this problem are based on supervised machine learning models trained from manually annotated examples. These models are affected by label sparsity, because the manual annotation of tweets is labour-intensive and time-consuming.

This thesis addresses the label sparsity problem for Twitter polarity classification by automatically building two type of resources that can be exploited when labelled data is scarce: opinion lexicons, which are lists of words labelled by sentiment, and synthetically labelled tweets.

In the first part of the thesis, we induce Twitter-specific opinion lexicons by training words level classifiers using representations that exploit different sources of information: (a) the morphological information conveyed by part-of-speech (POS) tags, (b) associations between words and the sentiment expressed in the tweets that contain them, and (c) distributional representations calculated from unlabelled tweets. Experimental results show that the induced lexicons produce significant improvements over existing manually annotated lexicons for tweet-level polarity classification.

In the second part of the thesis, we develop distant supervision methods for generating synthetic training data for Twitter polarity classification by exploiting unlabelled tweets and prior lexical knowledge. Positive and negative training instances are generated by averaging unlabelled tweets annotated according to a given polarity lexicon. We study different mechanisms for selecting the candidate tweets to be averaged. Our experimental results show that the training data generated by the proposed models produce classifiers that perform significantly better than classifiers trained from tweets annotated with emoticons, a popular distant supervision approach for Twitter sentiment analysis.

text: Acquiring and Exploiting Lexical Knowledge for Twitter Sentiment Analysis The most popular sentiment analysis task in Twitter is the automatic classification of tweets into sentiment categories such as positive, negative, and neutral. State-of-the-art solutions to this problem are based on supervised machine learning models trained from manually annotated examples. These models are affected by label sparsity, because the manual annotation of tweets is labour-intensive and time-consuming.

This thesis addresses the label sparsity problem for Twitter polarity classification by automatically building two type of resources that can be exploited when labelled data is scarce: opinion lexicons, which are lists of words labelled by sentiment, and synthetically labelled tweets.

In the first part of the thesis, we induce Twitter-specific opinion lexicons by training words level classifiers using representations that exploit different sources of information: (a) the morphological information conveyed by part-of-speech (POS) tags, (b) associations between words and the sentiment expressed in the tweets that contain them, and (c) distributional representations calculated from unlabelled tweets. Experimental results show that the induced lexicons produce significant improvements over existing manually annotated lexicons for tweet-level polarity classification.

In the second part of the thesis, we develop distant supervision methods for generating synthetic training data for Twitter polarity classification by exploiting unlabelled tweets and prior lexical knowledge. Positive and negative training instances are generated by averaging unlabelled tweets annotated according to a given polarity lexicon. We study different mechanisms for selecting the candidate tweets to be averaged. Our experimental results show that the training data generated by the proposed models produce classifiers that perform significantly better than classifiers trained from tweets annotated with emoticons, a popular distant supervision approach for Twitter sentiment analysis.

year: 2017

title: Filling out the picture: Wittgenstein on differences and alternatives

authors: Bowell, Tracy

subjects: Wittgenstein

abstract: At several points in his later writings Wittgenstein discusses imaginary forms of life and ways of thinking that appear queer or alien from our point of view; concepts so different from ours that those who think from within them seem to be alternatives to us. In this paper I argue that reflection on the notions of difference and possibility in play here shows that imaginary cases of alien conceptual schemes or forms of life such as those considered by Wittgenstein are not all cases of concepts that are entirely unintelligible for us; rather they may represent possible, albeit distant, ways of thinking for us. Such cases serve to aid imaginative reflection on our own case(s). By making us appreciate the possibility of the strange, they help us better to appreciate the arbitrariness of the familiar. I end the paper by considering what the implications of this reading of Wittgenstein's position might be for Donald Davidson's rejection of conceptual relativism.

text: Filling out the picture: Wittgenstein on differences and alternatives At several points in his later writings Wittgenstein discusses imaginary forms of life and ways of thinking that appear queer or alien from our point of view; concepts so different from ours that those who think from within them seem to be alternatives to us. In this paper I argue that reflection on the notions of difference and possibility in play here shows that imaginary cases of alien conceptual schemes or forms of life such as those considered by Wittgenstein are not all cases of concepts that are entirely unintelligible for us; rather they may represent possible, albeit distant, ways of thinking for us. Such cases serve to aid imaginative reflection on our own case(s). By making us appreciate the possibility of the strange, they help us better to appreciate the arbitrariness of the familiar. I end the paper by considering what the implications of this reading of Wittgenstein's position might be for Donald Davidson's rejection of conceptual relativism.

year: 2009

title: The timing of the human discovery and colonization of New Zealand

authors: Sutton, Douglas G.

abstract: In discriminating between the proposed Long, Short and Intermediate Chronologies for New Zealand prehistory, archaeologists have recently voted by a narrow majority that the human commensal, Rattus exulans, was present in New Zealand up to 2000 years BP, although the preferred date of ‘first settlement’ by people was ca 800 years BP. A recalibration of New Zealand chronometric data has resulted in reinterpretations of the date and duration of occupation on critical archaeological sites. A remodelling of the ages of the putatively earliest sites in New Zealand has shown these to indicate only a broadly defined period when settlement occurred rather than the date when New Zealand was discovered (as the Short Chronology advocates have insisted). Finally, comparisons with archaeological research on islands elsewhere in the world have brought with them recognition that the discovery, exploration, initial settlement and colonization of New Zealand by Polynesian voyagers were broadly consecutive processes. This paper reviews a range of current evidence in the context of its current theorization and affirms the Long Chronology, recognizing it as the most plausible hypothesis.

text: The timing of the human discovery and colonization of New Zealand In discriminating between the proposed Long, Short and Intermediate Chronologies for New Zealand prehistory, archaeologists have recently voted by a narrow majority that the human commensal, Rattus exulans, was present in New Zealand up to 2000 years BP, although the preferred date of ‘first settlement’ by people was ca 800 years BP. A recalibration of New Zealand chronometric data has resulted in reinterpretations of the date and duration of occupation on critical archaeological sites. A remodelling of the ages of the putatively earliest sites in New Zealand has shown these to indicate only a broadly defined period when settlement occurred rather than the date when New Zealand was discovered (as the Short Chronology advocates have insisted). Finally, comparisons with archaeological research on islands elsewhere in the world have brought with them recognition that the discovery, exploration, initial settlement and colonization of New Zealand by Polynesian voyagers were broadly consecutive processes. This paper reviews a range of current evidence in the context of its current theorization and affirms the Long Chronology, recognizing it as the most plausible hypothesis.

year: 2008