Connect with friends, family and other people you know. Das sei laut Facebook nicht neu. So, one can unzip the files, start MongoDB on your machine and use the following command to import the files in your MongoDB: We also provide Python 3 scripts that can be used to work with the data. Facebook data was collected from survey participants using this Facebook app. This work is to model the user patterns and to study the effectiveness of machine learning predictive modeling approaches on leading social networking service Facebook. The dataset contains 5 variants of the dataset, for the details about the variants and detailed analysis read and cite the research paper @INPROCEEDINGS{Sing1503:Comment, AUTHOR='Kamaljot Singh and Ranjeet Kaur Sandhu and Dinesh Kumar', TITLE='Comment Volume Prediction Using Neural Networks and Decision Trees', … The order to use when displaying comments. The task associated with the data is to predict how many comments the post will receive. Around 260,000 threads / comments scraped from Reddit. Next to Download Your Information, click View. Embedded comments are a simple way to put public post comments - by a Page or a person on Facebook - into the content of your web site or web page. } The research paper is also available at conference website: uksim.info/uksim2015/[Web Link] another extended paper is that is to be published soon is : @ARTICLE{Sing1601:Facebook, AUTHOR='Kamaljot Singh', TITLE='Facebook Comment Volume Prediction', JOURNAL='International Journal of Simulation- Systems, Science and Technology- IJSSST V16', ADDRESS='Cambridge, United Kingdom', DAYS=30, MONTH=jan, YEAR=2016, KEYWORDS='Neural Networks; RBF Network; Prediction; Facebook; Comments; Data Mining; REP Tree; M5P Trees. To automate the process, we developed a software prototype consisting of the crawler, Information extractor, information processor and knowledge discovery module. share|improve this answer|follow |. Copy & Paste HTML snippet ', ABSTRACT='The leading treads towards social networking services had drawn massive public attention from last one and half decade. 2 Page Checkins’s Decimal Encoding Page feature Describes how many individuals so far visited this place. ', ABSTRACT='The amount of data that is uploaded to social networking services is increasing day by day. 47-53 Base DateTime weekday Binary Encoding Weekdays feature This represents the day(Sunday...Saturday) on selected base Date/Time. The software calculated the sentiment with the efficiency of 100%. Description. The amount of data that is uploaded to these social networking services is increasing day by day. WhatsApp teilt Daten mit Facebook, allerdings mit einer Einschränkung. 34 CC5 Decimal Encoding Essential feature The difference between CC2 and CC3. Here are few good comments for Facebook profile pictures that can be used by anyone for free of cost to comment on different pictures uploaded on Facebook. 5 - 29 Derived Decimal Encoding Derived feature These features are aggregated by page, by calculating min, max, average, median and standard deviation of essential features. data-order-by. We modeled the user comment patters, over the posts on Facebook Pages and predicted that how many comments a post is expected to receive in next H hrs. The task associated with the data is to predict how many comments the post will receive. The user data is collected from Facebook based on their activities. This is a sparse data set, less than 10% of the attributes are used for each sample. Data Set Characteristics: Paper: Social Emotion Mining Techniques for Facebook Posts Reaction Prediction (accepted at ICAART 2018). If nothing happens, download GitHub Desktop and try again. Total 15 comments are collected. The Algorithm is applied on them. Also, while feature vectors from this dataset have been provided, the interpretation of those features has been obscured. We modeled the user comment patters, over the posts on Facebook Pages and predicted that how many comments a post is expected to receive in next H hrs. We modeled the user comment patters, over the posts on Facebook Pages and predicted that how many comments a post is expected to receive in next H hrs. We’ve built and are now sharing a dataset designed specifically to help AI researchers develop new systems to identify multimodal hate speech. Facebook has complicated, highly granular, poorly-documented privacy settings. This work is to model the user patterns and to study the effectiveness of machine learning predictive modeling approaches on leading social networking service Facebook. 3 Page talking about Decimal Encoding Page feature Defines the daily interest of individuals towards source of the document/ Post. Facebook has updated its hate speech algorithm, reversing years of neutrality to prioritize anti-black comments while making anti-white slurs the lowest priority. MongodbStorage inherits from DataStorage and contains the implemented database access (default database name is "research_project", the user should use as specified in the import command). We concluded that the Decision trees performed better than the Neural Networks under light of all evaluation metrics.' } this above paper will be freely available after publication at www.ijssst.info, @INPROCEEDINGS{Sing1503:Comment, AUTHOR='Kamaljot Singh and Ranjeet Kaur Sandhu and Dinesh Kumar', TITLE='Comment Volume Prediction Using Neural Networks and Decision Trees', BOOKTITLE='IEEE UKSim-AMSS 17th International Conference on Computer Modelling and Simulation, UKSim2015 (UKSim2015)', ADDRESS='Cambridge, United Kingdom', DAYS=25, MONTH=mar, YEAR=2015, KEYWORDS='Neural Networks; RBF Network; Prediction; Facebook; Comments; Data Mining; REP Tree; M5P Trees. This dataset was created for a research project at the Department of Data Science and Knowledge Engineering (Maastricht University). Step-by-Step 1. In the left column, click Your Facebook Information. You can find all the comments from May 2015 on scripts for natural language processing (NLP). Step 5:Scraping Facebook Group posts data such as Post statutes,Reactions count,Likes count,Shares count,comments count Scraping Facebook Open Public groups is similar to scraping Facebook pages.Make sure you have the Group numeric ID as explained in Step 3 and access token as explained in Step 2.Then run this Python script groups.py as explained in Step 4. } The research paper is also available at conference website: uksim.info/uksim2015/[Web Link] another extended paper is that is to be published soon is : @ARTICLE{Sing1601:Facebook, AUTHOR='Kamaljot Singh', TITLE='Facebook Comment Volume Prediction', JOURNAL='International Journal of Simulation- Systems, Science and Technology- IJSSST V16', ADDRESS='Cambridge, United Kingdom', DAYS=30, MONTH=jan, YEAR=2016, KEYWORDS='Neural Networks; RBF Network; Prediction; Facebook; Comments; Data Mining; REP Tree; M5P Trees. Learn what 's not on your Page using this Facebook app research project at the Department of data that uploaded... 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