5,345 research outputs found
The Development of a Temporal Information Dictionary for Social Media Analytics
Dictionaries have been used to analyze text even before the emergence of social media and the use of dictionaries for sentiment analysis there. While dictionaries have been used to understand the tonality of text, so far it has not been possible to automatically detect if the tonality refers to the present, past, or future. In this research, we develop a dictionary containing time-indicating words in a wordlist (T-wordlist). To test how the dictionary performs, we apply our T-wordlist on different disaster related social media datasets. Subsequently we will validate the wordlist and results by a manual content analysis. So far, in this research-in-progress, we were able to develop a first dictionary and will also provide some initial insight into the performance of our wordlist
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Analysing video and audio data: existing approaches and new innovations
Across many subject disciplines, video and audio data are recorded in order to document processes, procedures or interactions. These video and audio data are consequently analysed using a number of techniques, in order to try and make sense of what was happening at the time of the recording, sometimes in relation to initial hypotheses or sometimes in terms of a 'post hoc' analysis where a more grounded approach is used. This paper contains an overview of tools and techniques for examining video data and looks at potential new methods borrowed from the field of learning analytics, related to discourse analysis. Discourse analysis, where conversations and the spoken word are explored and dissected in detail, can provide us with information about the learning context and the ways in which learners interact with people and other resources in their environment
Characterizing Pedophile Conversations on the Internet using Online Grooming
Cyber-crime targeting children such as online pedophile activity are a major
and a growing concern to society. A deep understanding of predatory chat
conversations on the Internet has implications in designing effective solutions
to automatically identify malicious conversations from regular conversations.
We believe that a deeper understanding of the pedophile conversation can result
in more sophisticated and robust surveillance systems than majority of the
current systems relying only on shallow processing such as simple word-counting
or key-word spotting.
In this paper, we study pedophile conversations from the perspective of
online grooming theory and perform a series of linguistic-based empirical
analysis on several pedophile chat conversations to gain useful insights and
patterns. We manually annotated 75 pedophile chat conversations with six stages
of online grooming and test several hypothesis on it. The results of our
experiments reveal that relationship forming is the most dominant online
grooming stage in contrast to the sexual stage. We use a widely used
word-counting program (LIWC) to create psycho-linguistic profiles for each of
the six online grooming stages to discover interesting textual patterns useful
to improve our understanding of the online pedophile phenomenon. Furthermore,
we present empirical results that throw light on various aspects of a pedophile
conversation such as probability of state transitions from one stage to
another, distribution of a pedophile chat conversation across various online
grooming stages and correlations between pre-defined word categories and online
grooming stages
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A tool for enhancing MetaMap performance when annotating clinical guideline documents with UMLS concepts
We developed a tool that integrates the National Library of Medicine's MetaMap software with GATE, an open-source text an- alytics framework. The tool allows non-ASCII encoded documents of numerous formats to be annotated with UMLS concepts. We created a GATE pipeline to chunk cardiovascular disease guideline text into default segments (blank-line delimited), XML element content, sentences and phrases, which were sequentially submitted to MetaMap for annotation. XML element, sentence and phrase chunking allowed term extraction and mapping to be completed in around 1/3 of the time taken with de- fault chunking, although with slight loss of accuracy (F1.0s=0.94-0.99). However, phrase chunking allows more complex input to be processed in real time, which is not possible with the other approaches. We discuss the results in relation to use of MetaMap's --term processing option for generating pre- and post-coordinated mappings from composite phrases
An application of distributional semantics for the analysis of the Holy Quran
In this contribution we illustrate the methodology and the results of an experiment we conducted by applying Distributional Semantics Models to the analysis of the Holy Quran. Our aim was to gather information on the potential differences in meanings that the same words might take on when used in Modern Standard Arabic w.r.t. their usage in the Quran. To do so we used the Penn Arabic Treebank as a contrastive corpu
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