Sentiment and Authority Analysis in Conversational Content

This paper deals with mining conversational content from the social media. It focused on two issues: opinion and emotion classification and identification of authoritative reviewers. The paper also describes applications representing the results obtained in the given areas. Authority identification can be used by organizations to search for experts in their specific areas to employ them. The opinion and emotion analysis can be useful for providing decision-making support

A survey on opinion summarization technique s for social media

The volume of data on the social media is huge and even keeps increasing. The need for efficient processing of this extensive information resulted in increasing research interest in knowledge engineering tasks such as Opinion Summarization. This survey shows the current opinion summarization challenges for social media, then the necessary pre-summarization steps like preprocessing, features extraction, noise elimination, and handling of synonym features. Next, it covers the various approaches used in opinion summarization like Visualization, Abstractive, Aspect based, Query-focused, Real Time, Update Summarization, and highlight other Opinion Summarization approaches such as Contrastive, Concept-based, Community Detection, Domain Specific, Bilingual, Social Bookmarking, and Social Media Sampling. It covers the different datasets used in opinion summarization and future work suggested in each technique. Finally, it provides different ways for evaluating opinion summarization

Ubiikkiteknologian ja media-alan tulevaisuus : Muutoshaasteet journalismissa ja mediassa

Tässä tutkimusraportissa käsitellään ubiikkiteknologista murrosta ja sen vaikutuksia viestintään ja journalismiin. Tutkimustehtävä ei ole erityisen helppo, koska ubiikkiteknologian tuomat muutokset merkitsevät isoa systeemistä murrosta mediataloille, viestinnälle ja journalismille. Ubiikkiteknologia tulee vaikuttamaan mediataloihin itsessään, eri medioiden mobiilisuuteen ja median uutisaiheisiin ja niiden teknisiin käsittelytapoihin. Vaikutuksia tulee olemaan myös medioiden liiketoimintamalleihin ja ansaintalogiikkoihin. Ubiikkiteknologia tulee myös muuttamaan itse journalismia ja journalistista professiota. Ajallemme olennainen asia on ubiikkiteknologia ja tämän laajan teknologia-aallon aikaan saamat uudet ilmiöt. Yleisesti ilmaistuna ubiikkiteknologialla tarkoitetaan erilaisia laitteita ja koneita, jotka ymmärtävät ihmisen toimintaa ja reagoivat siihen. Ubiikkiteknologia mahdollistaa myös koneiden ja laitteiden välisen viestinnän (Machine-to-Machine Communication, lyh. M2MC)

Multidimensional opinion mining from social data

Social media popularity and importance is on the increase due to people using it for various types of social interaction across multiple channels. This thesis focuses on the evolving research area of Social Opinion Mining, tasked with the identification of multiple opinion dimensions, such as subjectivity, sentiment polarity, emotion, affect, sarcasm, and irony, from user-generated content represented across multiple social media platforms and in various media formats, like textual, visual, and audio. Mining people’s social opinions from social sources, such as social media platforms and newswires commenting sections, is a valuable business asset that can be utilised in many ways and in multiple domains, such as Politics, Finance, and Government. The main objective of this research is to investigate how a multidimensional approach to Social Opinion Mining affects fine-grained opinion search and summarisation at an aspect-based level and whether such a multidimensional approach outperforms single dimension approaches in the context of an extrinsic human evaluation conducted in a real-world context: the Malta Government Budget, where five social opinion dimensions are taken into consideration, namely subjectivity, sentiment polarity, emotion, irony, and sarcasm. This human evaluation determines whether the multidimensional opinion summarisation results provide added-value to potential end-users, such as policy-makers and decision-takers, thereby providing a nuanced voice to the general public on their social opinions on topics of a national importance. Results obtained indicate that a more fine-grained aspect-based opinion summary based on the combined dimensions of subjectivity, sentiment polarity, emotion, and sarcasm or irony is more informative and more useful than one based on sentiment polarity only. This research contributes towards the advancement of intelligent search and information retrieval from social data and impacts entities utilising Social Opinion Mining results towards effective policy formulation, policy-making, decision-making, and decision-taking at a strategic level