Sentiment analysis is the Natural Language Processing (NLP) task dealing with the detection and classification of sentiments in texts. While some tasks deal with identifying presence of sentiment in text (Subjectivity analysis), other tasks aim at determining the polarity of the text categorizing them as positive, negative and neutral. Whenever there is presence of sentiment in text, it has a s...

This paper presents Centre for Development of Advanced Computing Mumbai’s (CDACM) submission to the NLP Tools Contest on Part-Of-Speech (POS) Tagging For Code-mixed Indian Social Media Text (POSCMISMT) 2015 (collocated with ICON 2015). We submitted results for Hindi (hi), Bengali (bn), and Telugu (te) languages mixed with English (en). In this paper, we have described our approaches to the POS ...

Cyber Physical Social Sensing makes mobile social networks (MSNs) popular with users. However, such attacks are rampant as malicious URLs are spread covertly through quick response (QR) codes to control compromised accounts in MSNs to propagate malicious messages. Currently, there are generally two types of methods to identify compromised accounts in MSNs: one type is to analyze the potential t...

This article employs and extends the concept of technical code (Feenberg, 1992, 1995a, 1995b) to examine the current state of the internet. The notion of technical code – the cultural and social assumptions and values that become manifest in a technology’s physical and structural forms – is invoked to examine design characteristics of the internet that, in turn, reflect and provide opportunitie...

In this study, the problem of shallow parsing of Hindi-English code-mixed social media text (CSMT) has been addressed. We have annotated the data, developed a language identifier, a normalizer, a part-of-speech tagger and a shallow parser. To the best of our knowledge, we are the first to attempt shallow parsing on CSMT. The pipeline developed has been made available to the research community w...

Code-mixing is frequently observed in user generated content on social media, especially from multilingual users. The linguistic complexity of such content is compounded by presence of spelling variations, transliteration and non-adherance to formal grammar. We describe our initial efforts to create a multi-level annotated corpus of Hindi-English codemixed text collated from Facebook forums, an...

Conventional methods for tie prediction analysis in social media networks are often code-intensive and encompass complex steps. Against this backdrop, we used design science research to develop a no-code platform. Our evaluation indicates that the platform significantly reduces complexity and, depending on network size, also total time. Moreover, it maintains accuracy similar of conventional, m...

An evaluation metric is an absolute necessity for measuring the performance of any system and complexity of any data. In this paper, we have discussed how to determine the level of complexity of code-mixed social media texts that are growing rapidly due to multilingual interference. In general, texts written in multiple languages are often hard to comprehend and analyze. At the same time, in or...