SerkOw · August 29, 2015 14:01
diff --git a/AST_Group_Assignment_10 b/AST_Group_Assignment_10
 Assignment:
 
 Send me a link to gist where you answer the following question: What do you need in order to finish your component for portfolio 2


 In order to finish our component for the second portfolio we need the following  ideas and constructions to work:

 We want to integrate the Twitter Search API in the way that it is linked to a selection menu, which contains a predetermined list of stock market definitions/names of corporations/brand. This is a replacement of the initial idea of letting users type brand names that would then be converting these into stock market name versions and thereby initiating the stock price graph, which constitutes the second part of the component.
 The selected corporation/brand would then bring up results through the Search API. Possible data we can use here are the quantity of tweets related to selected brand. Of course, a sentiment analysis of the results would be preferable for the sake of doing digital humanities research, as we aim to relate sentiment to 
 The API data type chosen to be taking into account would then be used to visualise it through D3. Quantities of tweets could be presented in bar charts and sentiment could be presented by a line graph where three lines could be drawn for positive, negative or neutral sentiment. This visualisation would possible if chronological dimension is available for the tweets that are included in the sentiment analysis.

 As briefly mentioned earlier, the second part would be related to the selection in the first part of the component, namely the particular stock market name. The selection would initiate a request from Yahoo’s Finance API and would get (historical/chronological) stock price data back that can easily be visualised in a line graph. Based on the time dimension and possibilities of the Search API the, tweets of users and their sentiment can be related to the trend of the stock price of a brand.  Again, based on the sentiment results, it would be interesting to see whether a social media network like Twitter could be considered as a medium with predictive capabilities for financial market that are in fact also related to sentiment for their development.
	Assignment:

	Send me a link to gist where you answer the following question: What do you need in order to finish your component for portfolio 2


	In order to finish our component for the second portfolio we need the following ideas and constructions to work:

	We want to integrate the Twitter Search API in the way that it is linked to a selection menu, which contains a predetermined list of stock market definitions/names of corporations/brand. This is a replacement of the initial idea of letting users type brand names that would then be converting these into stock market name versions and thereby initiating the stock price graph, which constitutes the second part of the component.
	The selected corporation/brand would then bring up results through the Search API. Possible data we can use here are the quantity of tweets related to selected brand. Of course, a sentiment analysis of the results would be preferable for the sake of doing digital humanities research, as we aim to relate sentiment to
	The API data type chosen to be taking into account would then be used to visualise it through D3. Quantities of tweets could be presented in bar charts and sentiment could be presented by a line graph where three lines could be drawn for positive, negative or neutral sentiment. This visualisation would possible if chronological dimension is available for the tweets that are included in the sentiment analysis.

	As briefly mentioned earlier, the second part would be related to the selection in the first part of the component, namely the particular stock market name. The selection would initiate a request from Yahoo’s Finance API and would get (historical/chronological) stock price data back that can easily be visualised in a line graph. Based on the time dimension and possibilities of the Search API the, tweets of users and their sentiment can be related to the trend of the stock price of a brand. Again, based on the sentiment results, it would be interesting to see whether a social media network like Twitter could be considered as a medium with predictive capabilities for financial market that are in fact also related to sentiment for their development.