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Harmony is the aspect of music concerned with the structure, progression, and relation of chords. In Western tonal music each period had different rules and practices of harmony. Similarly some composers and musicians are recognised for their characteristic harmonic patterns which differ from the chord sequences used by other musicians of the same period or genre. This thesis is concerned with the automatic induction of the harmony rules and patterns underlying a genre, a composer, or more generally a 'style'. Many of the existing approaches for music classification or pattern extraction make use of statistical methods which present several limitations. Typically they are black boxes, can not be fed with background knowledge, do not take into account the intricate temporal dimension of the musical data, and ignore rare but informative events. To overcome these limitations we adopt first-order logic representations of chord sequences and Inductive Logic Programming techniques to infer models of style. We introduce a fixed length representation of chord sequences similar to n-grams but based on first-order logic, and use it to characterise symbolic corpora of pop and jazz music. We extend our knowledge representation scheme using context-free definite-clause grammars, which support chord sequences of any length and allow to skip ornamental chords, and test it on genre classification problems, on both symbolic and audio data. Through these experiments we also compare various chord and harmony characteristics such as degree, root note, intervals between root notes, chord labels and assess their characterisation and classification accuracy, expressiveness, and computational cost. Moreover we extend a state- of-the-art genre classifier based on low-level audio features with such harmony-based models and prove that it can lead to statistically significant classification improvements. We show our logic-based modelling approach can not only compete with and improve on statistical approaches but also provides expressive, transparent and musicologically meaningful models of harmony which makes it suitable for knowledge discovery purposes.

Research regarding public perceptions of the legitimacy and reasonableness of protest groups, as well as support for these groups and identification with their causes have been studied extensively. However, much is still to be investigated on perceptions of protest groups by way of public attitudes toward protest violence, likelihood of engagement in activism, and political alignment with conservative or liberal ideologies. This study aimed to assess perceptions and attitudes toward conservative and liberal protest groups’ use of violent and nonviolent behavior. Participants read a description of one of four protest groups, with each group varying by political affiliation (conservative or liberal) and use of violence (violent or nonviolent). Participants then completed measures of public solidarity with the protest group as well as favorability ratings and attitudes toward the group. Participants also completed measures assessing their beliefs about violence, their capacity for future activist engagement, and their political alignment with conservative and liberal values. Results indicated that violent protesting behavior elicited a higher rating for participant intentions for future activism, on average, as compared to nonviolent protesting behaviors. Additionally, those reading about liberal protest groups expressed higher levels of solidarity and more favorable attitudes toward protest groups, on average, than did those reading about conservative protest groups. Further research in the evaluation of support for and attitudes toward protest groups is critical to expanding knowledge on protest group and protest observer dynamics. In addition, exploration of personal views on violence, intentions to protest, and political identity will continue building understanding around public perceptions related to support for protest groups and their causes.

This comparative case study examines the actions that the Haitian and Dominican governments, respectively, have taken to develop and sustain tourism within their borders. My premise is that governments, through state institutions and policies, can implement branding strategies that impact and change existing country image perceptions. Expanding on the determinants of tourism demand literature, I present a theoretical framework for how government institutions collaborate to create a favorable country brand by investing in the development of functional benefits {public safety and infrastructure quality}. The functional benefits are then supplied to the mass tourist market, who demands them in order to visit, lodge and spend money in the country. The findings of this study confirm that a causal relationship exists between a country’s level of stability and tourism arrivals and receipts, further establishing this study’s theory that high levels of investment in infrastructure quality and nation branding can positively influence country image perception to generate arrivals and receipts. Surprise outcomes regarding crime’s impact on arrivals and receipts present future opportunities to advance the literature.