Posted: August 4th, 2022

Big data Analysis using Hadoop

Analysis Methodology, Data Analysis and Outcomes, Dialogue

Big data Analysis using Hadoop

The predictive energy of social media

Goals: Achieve perception into the predictive energy of social media by establishing correlations between the options of the data posted on on-line social media platforms and salient properties of a big real-life occasion of your selection.

Background: You’ll develop instruments to realize perception into salient options of a big previous or future real-life occasion (reminiscent of e.g., presidential or parliamentary elections, referenda, and so forth.) of your selection using a big dataset collected off a web based social media website, reminiscent of Twitter. For the needs of this mission, you’ll have entry to the 300G Twitter dataset comprising one month value of Twitter data posted in 2012, however you’re additionally inspired to suggest and use an alternate dataset of your individual supplied it’s sufficiently giant, appropriate for the studied drawback, and accepted by the supervisor). You might also take into account gathering real-time data using the general public APIs provided by a few of the present social media platforms, reminiscent of Twitter and Guardian.

You’ll use the instruments you constructed to research varied meta-data attributes related to the data (reminiscent of time, location, hashtags, and so forth.) in addition to properties of the content material (e.g., sentiment rating) to ascertain temporal, spatial, content-related, and different correlations between the real-life occasion you chose and the related social media properties. The report ought to mirror upon and draw common conclusions regarding the predictive energy of social media platforms in relation to the dynamics and outcomes of real-life occasions.

Your mission should use one or a mixture of the large-scale data engineering instruments you’ve got studied in CS5234. For instance, previous tasks have used Hadoop/MapReduce to establish tweets related to the studied occasion, extract the attributes of relevance, and assign sentiment scores to the posted statuses using varied Pure-Language Processing (NLP) methods, reminiscent of [O’Connor, 2010] and/or Stanford NLP libraries (http://nlp.stanford.edu/)

Data: You should have entry to the 300G Twitter dataset on the division’s cloud or might use an alternate dataset of your individual topic to the supervisor’s approval.

Instruments(Hadoop/MapReduce): The mission should use one or a mixture of the large-scale data engineering instruments studied in CS5234.

Early Deliverables

1. The exact specification of the mission objectives as agreed with the advisor together with data assortment and Assessment instruments, and methodologies you intend to make use of to realize the required objectives.

2. Intermediate report and applications displaying and reflecting upon preliminary findings.

Last Deliverables

1. The software program you constructed to realize the mission objectives.

2. The ultimate report will talk about methods and findings and supply

From the Professor, the Draft of the dissertation ought to be prepared on Wednesday, 09 August 2022

NB: 1. Chapters one and two will likely be supplied by way of e mail

2. Data set can even be despatched by way of e mail

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