![]() GT.user.followers_count AS FOLLOWERS_CT, GT.iends_count AS FRNDS_CT, GT.user.favourites_count AS FAV_CT, GT.user.statuses_count AS STS_CT, U_MEN.name as USR_MNTS, HASH_T.text as HASH_TAGS, GT.lang AS LANG, LOC.country AS CNTRY, GT. Install and involve the toolkit from GitHub in your Google Cloud projectĬonfigure the CRON job - Google Cloud SchedulerĬonfigure the dashboard, by connecting to the BigQuery database with DataStudioĬntext_entity_name AS CTX_ENTITY, ntext_domain_name AS CTX_DOMAIN_NAME, ntext_domain_id AS CTX_ID, entity.normalized_text as NER_TEXT,Ĭreated_at, entity.type as NER_TYPE, GT.text as TWT_TEXT, GT.tweet_url AS TWT_URL, GT.user.screen_name AS USR_SCR_NM, GT.er_url AS USR_URL, For example, you can analyze trends “60 minutes ago”, passing the time interval variable to the SQL query.Īs a user of this toolkit, you need to perform four steps:Īdd rules to the stream with the PowerTrack rules API endpoint Trends can be analyzed based on the time interval which can range from minutes to hours. Twitter: good for raising awareness about project and planning concepts. The time interval is a range (30 minutes, 60 minutes) that will be used to query the Tweets based on their creation time. purpose of the toolkit in mind, this would mean that local governments would. NEW DELHI: Bharatiya Janata Party (BJP) has accused the Congress party of creating a 'toolkit' that aims to tarnish the image of the country and Prime Minister Narendra Modi by calling the new strain of coronavirus as'India strain' or the 'Modi strain'. Google DataStudio is used to create a dashboard for trend detection and connects to the BigQuery via a SQL query with a time interval as a parameter. Google DataStudio as a Dashboard for analytics ![]() 500 Tweets per pull, configurable via config.js file), and store the Tweets in a BigQuery database. The Tweet loader service that gets triggered based on the CRON job will pull the Tweets in a batch mode (i.e. Also, this will act as a shield to protect the database from a huge number of ingesting calls to persist the Tweets.Ī CRON job based on Google Cloud Scheduler will act as a poller that will trigger the Tweet loader service at regular intervals. The PubSub topic will act as temporary storage for the Tweets and batch them for the Tweet loader service to store the Tweets in the database. When there is a sudden surge of Tweets, the toolkit can handle the increased volume of Tweets with the help of PubSub. ![]() The stream topic based on Google PubSub acts as a shock absorber for this architecture. The PowerTrack rules are governed by the PowerTrack Rules API. This means that you might wish to tweet several times a day so that you have more chance of your audience seeing your tweets. The Tweet streamer service is responsible for listening to the real-time Twitter PowerTrack API and pushes the Tweets temporarily to a Topic that is based on Google PubSub. Tweet streamer service (nodeJs component) This toolkit is comprised of 5 core components that are responsible for listening to real-time Tweets, pushing Tweets to a topic/queue, a CRON job that triggers a Tweet loader service which pulls the Tweets from the topic/queue to store them in a database, and, finally, Tweet visualization in a dashboard that connects to the database via a SQL query. ![]()
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