"Secretary in Fashion" and "Love-Letters": a study of socio-cultural and pragmatic-linguistic features in the late 17th century English language

Epistolary manuals are conspicuous historical documents for the pedagogy of letter writing; however, their actual usage as manuals by letter writers is unknown. "Secretary in Fashion" by Serre (1668), an epistolary manual, and "Love-Letters between a Nobleman and his Sister" (1684), an epistolary novel attributed to Behn, both give insights into epistolary conventions. Their inception and nature is interesting, considering their historical context. Despite the Restoration of Charles II, 17th century England was in a confused political state; as a result, texts regarding social convention or politics interested contemporary readers (the novel is inspired by a scandal of Lord Grey, an ardent Whig opposing Charles II). Past epistolary studies focus on 18th rather than 17th century manuals; the latter is typically used as supplementary information. Similarly, past epistolary fiction studies focus on 18th century texts; moreover, linguistic studies on Behn and the novel are deficient. Thus, this study addresses the research questions: 1) What are the socio-cultural and pragmaticlinguistic features represented in "Secretary in Fashion"? 2) What are the socio-cultural and pragmatic-linguistic features represented in "Love-Letters between a Nobleman and his Sister", and do any of these features correlate with the features represented in "Secretary in Fashion"? How far do the characteristic linguistic features of "Love-Letters between a Nobleman and his Sister" correlate with the practices recommended by the manual? Both texts were qualitatively analysed from an historical pragmatic perspective, which observes the potential effects of the socio-cultural and historical context. Also, as the texts concern shared discourses, comparisons were made with Gricean and Politeness Theory. The results show that the manual is a typical 17th century epistolary manual, aligning particularly with the "Academies of Complements", as it concerns the social conventions of the gentry. The novel mainly upheld instructions on form and matter; deviations occurred due to the amatory nature of some letters, and the narrative force affecting the style. Unfortunately, neither research question elucidates the actual usage of manuals. However, this study does show the epistolary practices of two writers, within specific contexts. It reveals that their 17th century English language use is affected by socialisation, in terms of social conventions concerning social rank, age, and gender; therefore, context varies language use. Also, their popularity reveals the interests of the 17th century society. Interest in epistolary-related texts, surely piques the interest of the modern reader as to why such epistolary-related texts were interesting.

Eighty years 'Owre the Sea': Robert Burns and the early United States of America, c. 1786-1866.

This thesis represents the first extensive critical study of the relationship between Robert Burns and the early United States of America. Spanning literature, history and memory studies, the following chapters take an interdisciplinary approach towards investigating the methods by which Burns and his works rose to prominence and came to be of cultural and literary significance in America. Theoretically, these converging disciplines intersect through a transnational, Atlantic Studies perspective that shifts emphasis from Burns as the 'national poet of Scotland' onto the various socio-cultural connections that facilitated the spread of his work and reputation. In addition to Scottish literary studies, the thesis contributes to the broader fields of Transatlantic, Transnational and American Studies. Previous studies have suggested that Burns's popularity in the early United States might be attributed to his kinship with 'national' American ideals of freedom, egalitarianism and individual liberty. While some of the evidence supports this claim, this thesis argues that it also wrongly assumes a spatiotemporal unity for the nineteenth-century American nation. It concludes by suggesting that future critical studies of the poet must heed the multifarious complexities of 'national' paradigms, pointing the way to further work on the reception and influence of Burns in other 'global' or, indeed, transnational contexts.

The role of context in image annotation and recommendation

With the rise of smart phones, lifelogging devices (e.g. Google Glass) and popularity of image sharing websites (e.g. Flickr), users are capturing and sharing every aspect of their life online producing a wealth of visual content. Of these uploaded images, the majority are poorly annotated or exist in complete semantic isolation making the process of building retrieval systems difficult as one must firstly understand the meaning of an image in order to retrieve it. To alleviate this problem, many image sharing websites offer manual annotation tools which allow the user to “tag” their photos, however, these techniques are laborious and as a result have been poorly adopted; Sigurbjörnsson and van Zwol (2008) showed that 64% of images uploaded to Flickr are annotated with < 4 tags. Due to this, an entire body of research has focused on the automatic annotation of images (Hanbury, 2008; Smeulders et al., 2000; Zhang et al., 2012a) where one attempts to bridge the semantic gap between an image’s appearance and meaning e.g. the objects present. Despite two decades of research the semantic gap still largely exists and as a result automatic annotation models often offer unsatisfactory performance for industrial implementation. Further, these techniques can only annotate what they see, thus ignoring the “bigger picture” surrounding an image (e.g. its location, the event, the people present etc). Much work has therefore focused on building photo tag recommendation (PTR) methods which aid the user in the annotation process by suggesting tags related to those already present. These works have mainly focused on computing relationships between tags based on historical images e.g. that NY and timessquare co-exist in many images and are therefore highly correlated. However, tags are inherently noisy, sparse and ill-defined often resulting in poor PTR accuracy e.g. does NY refer to New York or New Year? This thesis proposes the exploitation of an image’s context which, unlike textual evidences, is always present, in order to alleviate this ambiguity in the tag recommendation process. Specifically we exploit the “what, who, where, when and how” of the image capture process in order to complement textual evidences in various photo tag recommendation and retrieval scenarios. In part II, we combine text, content-based (e.g. # of faces present) and contextual (e.g. day-of-the-week taken) signals for tag recommendation purposes, achieving up to a 75% improvement to precision@5 in comparison to a text-only TF-IDF baseline. We then consider external knowledge sources (i.e. Wikipedia & Twitter) as an alternative to (slower moving) Flickr in order to build recommendation models on, showing that similar accuracy could be achieved on these faster moving, yet entirely textual, datasets. In part II, we also highlight the merits of diversifying tag recommendation lists before discussing at length various problems with existing automatic image annotation and photo tag recommendation evaluation collections. In part III, we propose three new image retrieval scenarios, namely “visual event summarisation”, “image popularity prediction” and “lifelog summarisation”. In the first scenario, we attempt to produce a rank of relevant and diverse images for various news events by (i) removing irrelevant images such memes and visual duplicates (ii) before semantically clustering images based on the tweets in which they were originally posted. Using this approach, we were able to achieve over 50% precision for images in the top 5 ranks. In the second retrieval scenario, we show that by combining contextual and content-based features from images, we are able to predict if it will become “popular” (or not) with 74% accuracy, using an SVM classifier. Finally, in chapter 9 we employ blur detection and perceptual-hash clustering in order to remove noisy images from lifelogs, before combining visual and geo-temporal signals in order to capture a user’s “key moments” within their day. We believe that the results of this thesis show an important step towards building effective image retrieval models when there lacks sufficient textual content (i.e. a cold start).