A5050277461- Topic Modeling
- Advanced Text Analysis Techniques
- Speech and dialogue systems
- Expert finding and Q&A systems
- Natural Language Processing Techniques
- AI in Service Interactions
- Sentiment Analysis and Opinion Mining
- Misinformation and Its Impacts
- Hate Speech and Cyberbullying Detection
- Information Retrieval and Search Behavior
- Public Relations and Crisis Communication
- Spam and Phishing Detection
- Authorship Attribution and Profiling
- Social Media and Politics
- Text and Document Classification Technologies
- Mobile Crowdsensing and Crowdsourcing
- Complex Network Analysis Techniques
- Social Robot Interaction and HRI
- Recommender Systems and Techniques
- Open Education and E-Learning
- Usability and User Interface Design
- Text Readability and Simplification
- Generative Adversarial Networks and Image Synthesis
- Names, Identity, and Discrimination Research
- Vehicular Ad Hoc Networks (VANETs)
San Jose State University
2021-2024
Human Computer Interaction (Switzerland)
2022
Rutgers, The State University of New Jersey
2017-2019
Rutgers Sexual and Reproductive Health and Rights
2019
Jadavpur University
2015-2018
As human beings utilize computing technologies to mediate multiple aspects of their lives, cyberbullying has grown as an important societal challenge. Cyberbullying may lead deep psychiatric and emotional disorders for those affected. Hence, there is urgent need devise automated methods detection prevention. While recent efforts have defined sophisticated text processing detection, are yet few that leverage visual data automatically detect cyberbullying. Based on early analysis a public,...
In this paper, we investigate the relationship between searching and learning, by conceptualizing information seeking as a learning process, an outcome of process. We present participants with four search tasks, each them designed to represent different cognitive levels learning. Through quantitative analysis participants» Web logs, examine how individual behavior is influenced task complexity tasks in hierarchical order. also explore perceived outcomes processes, actions, are related...
ABSTRACT The interaction of technology with humans has many adverse effects. rapid growth and outreach the social media Web have led to dissemination questionable untrusted content among a wider audience, which negatively influenced their lives judgment. Many research studies been conducted tackle detection spreading fake news, is misinformation that looks genuine. While first step such tasks would be classify claims associated based on credibility, next steps involve identifying hidden...
Introduction. As large language models (LLMs), such as GPTs, become more intelligent, a key area of exploration is how these technologies can improve the customer experience. Contrary to common belief, many consumers, including Gen Z, prefer human-provided service, illustrating importance human-AI collaboration in space. Method. By leveraging author’s real-world knowledge enterprise management and service delivery, we reviewed numerous literature about AI, management, design synthesised...
A common step in the processing of any text is part-of-speech tagging input text.In this paper, we present an approach to tackle code-mixed from three different languages Bengali, Hindi, and Tamilapart English.Our system uses Conditional Random Field, a sequence learning method, which useful capture patterns sequences containing code switching tag each word with accurate information.We have used various pre-processing post-processing modules improve performance our system.The results were...
Sentiment analysis is the Natural Language Processing (NLP) task dealing with detection and classification of sentiments in texts. While some tasks deal identifying presence sentiment text (Subjectivity analysis), other aim at determining polarity categorizing them as positive, negative neutral. Whenever there a text, it has source (people, group people or any entity) directed towards entity, object, event person. to determine subject, target valence sentiment. In our work, we try...
The Future Conversations workshop at CHIIR'21 looked to the future of search, recommendation, and information interaction ask: where are opportunities for conversational interactions? What do we need get there? Furthermore, who stands benefit? was hands-on interactive. Rather than a series technical talks, solicited position statements on opportunities, problems, solutions in search all modalities (written, spoken, or multimodal). This paper -co-authored by organisers participants workshop-...
Authorship attribution, being an important problem in many areas in-cluding information retrieval, computational linguistics, law and journalism etc., has been identified as a subject of increasingly research interest the re-cent years. In case Author Identification task PAN at CLEF 2015, main focus was given on cross-genre cross-topic author verification tasks. We have used several word-based style-based features to identify dif-ferences between known unknown problems one set label ones...
An evaluation metric is an absolute necessity for measuring the performance of any system and complexity data. In this paper, we have discussed how to determine level code-mixed social media texts that are growing rapidly due multilingual interference. general, written in multiple languages often hard comprehend analyze. At same time, order meet demands analysis, it also necessary a particular document or text segment. Thus, present existing metrics determining code-mixing corpus, their...
Sentiment analysis has proven to be a popular research area for analyzing social media texts, newspaper articles, and product reviews. However, sentiment of citation instances is relatively unexplored research. For scientific papers, it often assumed that the associated with inherently positive. This assumption due hedged nature in citations, which difficult identify classify. As result, most existing indexes focus only on frequency citation. In this paper, we highlight importance...
In an information seeking episode, users often look for sources in online and offline environments depending on the task at hand. However, most times consider factors such as ease, time taken to complete task, number of be consulted essential while fulfilling task. our study, we explore role different cost variables -- explored based cognitive complexity levels, from Bloom»s taxonomy, by conducting a user study. We study search behaviors shown levels three variables. observed intriguing...
The interaction of technology with humans have many adverse effects. rapid growth and outreach the social media Web led to dissemination questionable untrusted content among a wider audience, which has negatively influenced their lives judgment. Different election campaigns around world highlighted how ''fake news'' - misinformation that looks genuine can be targeted towards specific communities manipulate confuse them. Ever since, automatic fake news detection gained widespread attention...
This paper describes our approach on Query Word Labeling as an attempt in the shared task Mixed Script Information Retrieval at Forum for Evaluation (FIRE) 2015. The query is written Roman script and words were English or transliterated from Indian regional languages. A total of eight languages present addition to English. We also identified Named Entities special symbols part task. CRF based machine learning framework was used labeling individual with their corresponding language labels. a...
ABSTRACT Twitter has emerged as an important forum for discussion among academic librarians. In this research, we take a mixed‐methods approach to study the thematic content and sentiment of tweets authored by librarians in United States, Canada, Kingdom. We found differences semantic themes present data from each country that point how engage on Twitter. While more work remains be done, cast new light members professional communities use social media. Our qualitative analysis identified 11...
Recent developments in conversational IR have raised questions about the nature of interactions which occur between user and system cognitive capabilities expected such systems. In our research, we investigate completeness existing theoretical frameworks explaining search data propose modifications to The linear transient speech makes it cognitively challenging for process a large amount information. We study evaluate users' preference modalities when using will help us understand how...
In recent years, Community Question Answering (CQA) has emerged as a popular platform for knowledge curation and archival. An interesting aspect of question answering is that it combines aspects from natural language processing, information retrieval, machine learning. this paper, we have explored how the depth neural network influences accuracy prediction deleted questions in question-answering forums. We used different shallow deep models analyzed relationships between number hidden...
Understanding human spoken dialogues in an information-seeking scenario is a significant challenge for IR researchers. Prior literature intelligent systems suggests that by identifying speech acts dialogues, we can identify the search intent and information needs of user. Therefore, this paper, have used to address problem natural language understanding conversational systems. First, collected human-system interaction data through Wizard-of-Oz study. Next, developed gold-standard dataset...
ABSTRACT In this paper, we describe the different search behaviors exhibited by participants while performing learning‐oriented tasks. The tasks have been designed to represent cognitive levels of learning hierarchically. We investigate how searcher's behavior and perceived outcomes vary with increasing complexity. study, analyze log data participants, self‐reports, questionnaires interviews both descriptively statistically. Our results suggest that topic knowledge interest difficulty...
ABSTRACT Searching as learning work is growing in interest, however definitions of ‘learning’ this space have been somewhat narrow. Here we propose a panel sponsored by SIG InfoLearn that will feature presentations from three scholars whose falls the domain “searching learning,” followed synthesis presented fourth scholar along with one panelists, who draw key conceptual intersections among empirical research papers and then explicate linkages to existing sciences has potential further...
Whenever human beings interact with each other, they exchange or express opinions, emotions, and sentiments. These opinions can be expressed in text, speech images. Analysis of these sentiments is one the popular research areas present day researchers. Sentiment analysis, also known as opinion mining tries to identify classify into two broad categories - positive negative. In recent years, scientific community has taken a lot interest analyzing sentiment textual data available various social...
Advice forums are a crowdsourced way to reinforce cultural norms and moral behavior.Sites like Reddit contain massive amounts of natural language human interaction, with rules unique each individual subreddit community.To explore this data, we created dataset top 1000 posts from two such forums, r/AmItheAsshole r/relationships, extracted features including sentiment, similarity, word frequency, demographics using both algorithmic manual methods.Further, developed method extract demographic...