1. This project is co-funded by the European Union T2.4: Social Media Data Capturing Module Brussels, 16 December 2014

2. Introduction The development of the Social Media data capturing module outlined in Task 2.4, is part of the general architecture for the DSS.

3. The module captures targeted information from building occupants, regarding comfort levels, indoor conditions’ rating, demands upon the premises they live in and the facilities they use. Challenges:  Extract unstructured data  Convert user generated content into knowledge  Evaluate actions based on that knowledge Introduction Social media provide huge amount of unstructured information In that way, the municipal authorities will be able to evaluate and assess the effectiveness of implemented action plans and the level of occupants’ acceptance.

4. Analysis Physical architecture of the social data capturing module Further processing is required in order to create the Meta information that will be fed to the DSS. This is the sentiment analysis on the messages that will categorize the message as: positive, negative or neutral It will also assign specific criteria to the content. Using this metadata, the system will be able to derive trends of typical behavioral habits of building occupants, in order to test and modify action plans.

5. Design Architecture Message Manipulation service corrects typical misspellings removes unrelated content information (e.g. media). anonymizes the messages to make users unidentifiable (username and URLs removal) Facebook social media adapter typical example of polling - driven adapter that is initiated in regular intervals in order to query for new messages Twitter social media adapter typical example of event - driven adapter that is initiated with an event: receipt of notifications on oncoming messages Configuration parser processes an incoming configuration file and extracts a dictionary with the configuration values. The INI standard has been selected as the format of the configuration file.

6. Design Architecture Event logger aggregates and filters various events and notifications and outputs them in the configured log file. Configuration file RDF formatter converts an incoming unified social message that complies with the IUnifiedSocialMessage interface to the RDF triplets that need to be sent to the DSS server Ztreamy client performs the http connection to the DSS ztreamy server and delivers via a POST operation the triplets payload. Message Filtering service excludes messages that are either not related to the Optimus DSS or that contain inappropriate words. Use of a black listing pattern matching algorithm that matches the messages against predefined black list dictionary and excludes them if a match is found

7. Pilot Configuration Each pilot will have a different social data capturing module installed. Physical location of the module is independent to the pilot, as the input sources are accessible from anywhere. The difference between each pilot is the configuration file that will be used for each module. Town Hall: Facebook page, Twitter account and a private social network Theatre: Facebook page, Twitter account For the purposes of this pilot, two social data capturing modules will be installed, one for each building. Moreover, the private social network api is being investigated in order to create yet another social media adapter that will be able to process that user input. Colombo-Pertini school, does not currently have a Facebook page or Twitter account. Occupants are mainly students with limited access to social media during their stay, the particular module might not apply to this pilot. This will be verified again with Savona on a later project phase. Strong social presence: Facebook page and Twitter account. The social data capturing module will be of important use in the case of Zaanstad: Occupants of the Town Hall are already engaged in social media exploitation within the building, using Yammer, a private social network. The Yammer adapter is being investigated. Implementation will be based on the polling driven model. Current & Future social presence: Savona Zaanstad Sant Cugat

8. Conclusions  The social data capturing module is responsible to capture targeted information from building occupants, regarding comfort levels, indoor conditions’ rating, demands upon the premises they live in and the facilities they use.  This information is processed and sent to the Optimus DSS server using a standard RDF message.  The component based architecture of this module ensures that it can be easily expanded to support more social media types.  The messages will be further analyzed and clustered into categories of expressed sentiment, namely of a positive, negative or neutral one at a post-processing stage on the DSS server. In this way: the messages will be converted into useful feedback on implemented action plans that will be taken into consideration in the evaluation process the data capturing module remains lightweight and can be deployed on any device.  The success of the social data capturing module is highly dependent on each pilot’s social media presence. Although the technical message receiving and parsing is complete, the pilots will have to do social media campaigns in order to motivate the building residents to engage in the social media and express their opinions.

9. Dr. Haris Doukas National Technical University of Athens 9, Iroon Polytechniou str., 157 80, Athens, GREECE Tel. +30 210 7722083 Fax +30 210 772 3550 E-mail: h_doukas@epu.ntua.gr Prof. John Psarras National Technical University of Athens 9, Iroon Polytechniou str., 157 80, Athens, GREECE Tel. +30 210 7723551 Fax +30 210 772 3550 E-mail: john@epu.ntua.gr