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Public Disputation, Power, and Social Order in Late Antiquity
Richard Lim explores the importance of verbal disputation in Late Antiquity, offering a rich socio-historical and cultural examination of the philosophical and theological controversies. He shows how public disputation changed with the advent of Christianity from a means of discovering truth and self-identification to a form of social competition and \"winning over\" an opponent. He demonstrates how the reception and practice of public debate, like other forms of competition in Late Antiquity, were closely tied to underlying notions of authority, community and social order. This title is part of UC Press's Voices Revived program, which commemorates University of California Press's mission to seek out and cultivate the brightest minds and give them voice, reach, and impact. Drawing on a backlist dating to 1893, Voices Revived makes high-quality, peer-reviewed scholarship accessible once again using print-on-demand technology. This title was originally published in 1995.
eBook
Multilingual text categorization and sentiment analysis: a comparative analysis of the utilization of multilingual approaches for classifying twitter data
Text categorization and sentiment analysis are two of the most typical natural language processing tasks with various emerging applications implemented and utilized in different domains, such as health care and policy making. At the same time, the tremendous growth in the popularity and usage of social media, such as Twitter, has resulted on an immense increase in user-generated data, as mainly represented by the corresponding texts in users’ posts. However, the analysis of these specific data and the extraction of actionable knowledge and added value out of them is a challenging task due to the domain diversity and the high multilingualism that characterizes these data. The latter highlights the emerging need for the implementation and utilization of domain-agnostic and multilingual solutions. To investigate a portion of these challenges this research work performs a comparative analysis of multilingual approaches for classifying both the sentiment and the text of an examined multilingual corpus. In this context, four multilingual BERT-based classifiers and a zero-shot classification approach are utilized and compared in terms of their accuracy and applicability in the classification of multilingual data. Their comparison has unveiled insightful outcomes and has a twofold interpretation. Multilingual BERT-based classifiers achieve high performances and transfer inference when trained and fine-tuned on multilingual data. While also the zero-shot approach presents a novel technique for creating multilingual solutions in a faster, more efficient, and scalable way. It can easily be fitted to new languages and new tasks while achieving relatively good results across many languages. However, when efficiency and scalability are less important than accuracy, it seems that this model, and zero-shot models in general, can not be compared to fine-tuned and trained multilingual BERT-based classifiers.
Journal Article
Nine days in May : the battles of the 4th Infantry Division on the Cambodian border, 1967
\"Reconstructs the prolonged, deadly encounter between three American battalions and two North Vietnamese Army regiments. On May 18, 1967 the 4th Infantry Division engaged in a nine day series of bloody battles in the Ia Tchar Valley and the remote jungle west of Pleiku as part of Operation Francis Marion\"-- Provided by publisher.
Book
Iphicrates, (Re)foundation of Drys, and Athenian Activity in the Northern Aegean in the 4th Century B.C
This paper elaborates on a curious episode in the career of Iphicrates—famous Athenian strategos and mercenary commander in the first half of the 4th century B.C. According to Theopompus [FGrH 115 F 161], Iphicrates was somehow involved in a settlement of the Thracian town of Drys. His presence there is also corroborated by a testimony of Demosthenes [XXIII 131–132], but the rhetor does not precise what Iphicrates’ exactly did there. Both sources mentioned above, as well as several others, will be re-examined in this article, eventually leading to a proposal of a different interpretation of Theopompus account and the entire historical episode. Namely, the article suggests that the relevant fragment of Hellenica should be understood as a reference to the reconstruction program of Drys conducted or at least initiated by Iphicrates. The town had presumably suffered some downfall before, which could have been a result of an engagement between Spartans and Athenians, as described by Polyaenus. This event is often placed by modern scholars around the year 375 B.C., although this article opts for an earlier period, one contemporary with the Corinthian War. This way, Iphicrates could have been involved in the re-settlement of the town in the second half of 380s, after he has married a princess of Seuthes’ family. Furthermore, it is suggested that the title of Anaxandrides’ fragmentarily preserved comedy “Protesilaos” was considered by the author to be a reference to Iphicrates and his activities in Thrace.
Journal Article
Speech emotion recognition and text sentiment analysis for financial distress prediction
In recent years, there has been an increasing interest in text sentiment analysis and speech emotion recognition in finance due to their potential to capture the intentions and opinions of corporate stakeholders, such as managers and investors. A considerable performance improvement in forecasting company financial performance was achieved by taking textual sentiment into account. However, far too little attention has been paid to managerial emotional states and their potential contribution to financial distress prediction. This study seeks to address this problem by proposing a deep learning architecture that uniquely combines managerial emotional states extracted using speech emotion recognition with FinBERT-based sentiment analysis of earnings conference call transcripts. Thus, the obtained information is fused with traditional financial indicators to achieve a more accurate prediction of financial distress. The proposed model is validated using 1278 earnings conference calls of the 40 largest US companies. The findings of this study provide evidence on the essential role of managerial emotions in predicting financial distress, even when compared with sentiment indicators obtained from text. The experimental results also demonstrate the high accuracy of the proposed model compared with state-of-the-art prediction models.
Journal Article