Carlo Aliprandi

Bio: Carlo Aliprandi is an academic researcher. The author has contributed to research in topics: The Internet & Open-source intelligence. The author has an hindex of 7, co-authored 14 publications receiving 297 citations.

Sentiment Analysis on Social Media

Abstract: The Web is a huge virtual space where to express and share individual opinions, influencing any aspect of life, with implications for marketing and communication alike. Social Media are influencing consumersa preferences by shaping their attitudes and behaviors. Monitoring the Social Media activities is a good way to measure customersa loyalty, keeping a track on their sentiment towards brands or products. Social Media are the next logical marketing arena. Currently, Facebook dominates the digital marketing space, followed closely by Twitter. This paper describes a Sentiment Analysis study performed on over than 1000 Facebook posts about newscasts, comparing the sentiment for Rai - the Italian public broadcasting service - towards the emerging and more dynamic private company La7. This study maps study results with observations made by the Osservatorio di Pavia, which is an Italian institute of research specialised in media analysis at theoretical and empirical level, engaged in the analysis of political communication in the mass media. This study takes also in account the data provided by Auditel regarding newscast audience, correlating the analysis of Social Media, of Facebook in particular, with measurable data, available to public domain.

KAF: a Generic Semantic Annotation Format

Abstract: We present KAF, the KYOTO Annotation Format. KAF is a layered and extendible linguistic annotation format that is specifically developed to arrive at semantic interoperability. KAF is used in seven languages in several applications throughout the KYOTO (Knowledge Yielding Ontologies for Transition-based Organization) project. The goal of these applications is to derive semantic data from linguistically processed text. Separate annotation layers are defined for each annotation process but these can be combined to arrive at a higher level of semantic representation. This paper gives an outline of KAF and a description of how it is applied in the KYOTO project.

Automating live and batch subtitling of multimedia contents for several European languages

Abstract: The subtitling demand of multimedia content has grown quickly over the last years, especially after the adoption of the new European audiovisual legislation, which forces to make multimedia content accessible to all. As a result, TV channels have been moved to produce subtitles for a high percentage of their broadcast content. Consequently, the market has been seeking subtitling alternatives more productive than the traditional manual process. The large effort dedicated by the research community to the development of Large Vocabulary Continuous Speech Recognition (LVCSR) over the last decade has resulted in significant improvements on multimedia transcription, becoming the most powerful technology for automatic intralingual subtitling. This article contains a detailed description of the live and batch automatic subtitling applications developed by the SAVAS consortium for several European languages based on proprietary LVCSR technology specifically tailored to the subtitling needs, together with results of their quality evaluation.

SAVAS: Collecting, Annotating and Sharing Audiovisual Language Resources for Automatic Subtitling

Abstract: This paper describes the data collection, annotation and sharing activities carried out within the FP7 EU-funded SAVAS project. The project aims to collect, share and reuse audiovisual language resources from broadcasters and subtitling companies to develop large vocabulary continuous speech recognisers in specific domains and new languages, with the purpose of solving the automated subtitling needs of the media industry.

Mining the Web to Monitor the Political Consensus

Abstract: Communication is becoming more and more crucial in the competitive political arena: politicians can monitor electors’ suggestions or claims, or the perception they might have about leaders’ statements, by analyzing blogs, newsgroups and newspapers. They try to take account of the complexity of public views in order to design populist measures and increase dramatically their consensus. The Web sources are more accessible, ubiquitous, and valuable than ever before. But the most valuable information is often hidden and encoded in blog posts or pages, which are often neither structured, nor classified, being free textual. The process of accessing all these raw data, heterogeneous in terms of source and lexicon, and transforming them into information is therefore strongly linked to automatic textual analysis and conceptual synthesis. This paper describes a Sentiment Mining study performed on over 1,000 news articles or forum/blog posts, concerning the Italian Prime Minister Silvio Berlusconi, involved in the escorts’ scandal.

Sentiment Analysis on Social Media

Abstract: The Web is a huge virtual space where to express and share individual opinions, influencing any aspect of life, with implications for marketing and communication alike. Social Media are influencing consumersa preferences by shaping their attitudes and behaviors. Monitoring the Social Media activities is a good way to measure customersa loyalty, keeping a track on their sentiment towards brands or products. Social Media are the next logical marketing arena. Currently, Facebook dominates the digital marketing space, followed closely by Twitter. This paper describes a Sentiment Analysis study performed on over than 1000 Facebook posts about newscasts, comparing the sentiment for Rai - the Italian public broadcasting service - towards the emerging and more dynamic private company La7. This study maps study results with observations made by the Osservatorio di Pavia, which is an Italian institute of research specialised in media analysis at theoretical and empirical level, engaged in the analysis of political communication in the mass media. This study takes also in account the data provided by Auditel regarding newscast audience, correlating the analysis of Social Media, of Facebook in particular, with measurable data, available to public domain.

Social media sentiment analysis based on COVID-19

Abstract: In today's world, the social media is everywhere, and everybody come in contact with it every day. With social media datas, we are able to do a lot of analysis and statistics nowdays. Within this s...

IXA pipeline: Efficient and Ready to Use Multilingual NLP tools

Abstract: IXA pipeline is a modular set of Natural Language Processing tools (or pipes) which provide easy access to NLP technology. It offers robust and efficient linguistic annotation to both researchers and non-NLP experts with the aim of lowering the barriers of using NLP technology either for research purposes or for small industrial developers and SMEs. IXA pipeline can be used “as is” or exploit its modularity to pick and change different components. Given its open-source nature, it can also be modified and extended for it to work with other languages. This paper describes the general data-centric architecture of IXA pipeline and presents competitive results in several NLP annotations for English and Spanish.

The state of the art in sentiment visualization

Abstract: Visualization of sentiments and opinions extracted from or annotated in texts has become a prominent topic of research over the last decade. From basic pie and bar charts used to illustrate customer reviews to extensive visual analytics systems involving novel representations, sentiment visualization techniques have evolved to deal with complex multidimensional data sets, includingtemporal, relational, and geospatial aspects. This contribution presents a survey of sentiment visualization techniques based on a detailed categorization. We describe the background of sentiment analysis, introduce a categorization for sentiment visualization techniques that includes 7 groups with 35 categories in total, and discuss 132 techniques from peer-reviewed publications together with an interactive web-based survey browser. Finally, we discuss insights and opportunities for further research in sentiment visualization. We expect this survey to be useful for visualization researchers whose interests include sentiment or other aspects of text data as well as researchers and practitioners from other disciplines in search of efficient visualization techniques applicable to their tasks and data. (Less)