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This article attempts to answer the phenomenological question, "What does it mean to be a qualitative researcher?" and an ancillary question, "What does 'making meaning' mean?" The author, in collaboration with selected participants at the 2018 The Qualitative Report and the International Institute for Qualitative Methodology's Qualitative Research Methods conferences, proposes that research is devotion. Three major categories or components of devotion are purpose (personal and professional validation), belonging (communal grounding), and meaning (an enriched life). Ten subcategories or "elements of style" as qualitative researchers include: meticulous vigilance of details, unyielding resiliency, visionary reinvention, social savvy, humble vulnerability, representational responsibility, finding your methodological tribes, emotional immersion, gifting your ideas, and knowing and understanding yourself.

The Naval Message Analyzer was developed to show that a distributed computerized message-analysis system could be built using the CODER (COmposite Document Expert!/extended/effective Retrieval) system, a testbed for artificial intelligence methods in Information Storage and Retrieval, as the foundation of the project. The Naval Message Analyzer reads messages contained in disk files and indexes them according to dates, locations and words. Words are used as indexes to documents according to headword entries in the Collins English Dictionary. Dates, sources and destinations are read from the header information as well as the body of each message. Header information is in one standard format, but other information is detected using clues within the text, and is further analyzed by expert modules. A database of world-knowledge is included as a repository of proper names for ships, cities, countries and abbreviations. A database maintenance facility is an integral part of the Naval Message Analyzer, so that facts can be added or changed as necessary. The system retrieves the closest matches, in descending order, to one or more ship names, locations, dates and keywords provided by the user. ; Master of Science

Twitter is the most requested microblog site with 336million active users. On Twitter, users can instantly express ideas, emotions and reactions with tweets. Data coming from twitter is fast and effective responses can be obtained,whichcanbeusedin political, social and economic areas. It is possible to analyze the characteristics, trends and behaviors of the users by revealing their interaction. In this study, a brief description of methodology used to analyze the Twitter account/Profile of an individual based on the tweets tweeted by user along with sentiment analysis of the same is presented.Twitterprofile analysis by parsing the tweets fetched from Twitter using Python isdiscussed.