Social media measurement

Social media measurement or 'social media monitoring' is a way of computing popularity of a brand or company by extracting information from social media channels,[1] such as blogs, wikis, news sites, micro-blogs such as Twitter, social networking sites, video/photo sharing websites, forums, message boards and user-generated content from time to time.[2] In other words, this is the way to caliber success of social media marketing strategies used by a company or a brand.[3] It is also used by companies to gauge current trends in the industry.[4] The process first gathers data from different websites and then performs analysis based on different metrics like time spent on the page, click through rate, content share, comments, text analytics to identify positive or negative emotions about the brand.[5][6]

Social Media Measurement process starts with defining a goal that needs to be achieved and defining expected outcome of the process. The expected outcome varies per the goal and is usually measured by variety of metrics. This is followed by defining possible social strategies to be used to achieve the goal. Then the next step is designing strategies to be used and setting up configuration tools which eases the process of collecting the data. In next step, strategies and tools are deployed in real time. This step involves conducting Quality Assurance tests of the methods deployed to collect the data. And in final step, data collected from the system is analyzed and if need arises, is refined on the run time to enhance the methodologies used. The last step ensures that the result obtained is more aligned with the goal defined in the first step.[7]

Data Acquisition

Acquiring data from social media is in demand of an exploring the user participation and population with the purpose of retrieving and collecting so many kinds of data(ex: comments, downloads etc.).[8] There are several prevalent techniques to acquire data such as Network traffic analysis, Ad-hoc application and Crawling[9]

Network Traffic Analysis - Network traffic analysis is the process of capturing network traffic and observing it closely to determine what is happening in the network. It is primarily done to improve the performance, security and other general management of the network.[10] However concerned about the potential tort of privacy on the Internet, network traffic analysis is always restricted by the government. Furthermore, high speed links are not adaptable to traffic analysis because the possible overload problem according to the packet sniffing mechanism [11]

Ad-hoc Application - Ad-hoc application is a kind of application that provide services and games to social network users by developing the APIs offered by social network company(Facebook Developer Platform). The infrastructure of Ad-hoc application allow the user to interact with the interface layer instead of the application servers. The API provide path for application to access information after the user login.[12] Moreover, the size of the data set collected vary with the popularity of the social media platform i.e social media platforms having high number of users will have more data than platforms having less user base.[12] Scraping is a process in which the APIs collect online data from the social media. The data collected from Scraping is in raw format. However, having access to these type data is a bit difficult because of its commercial value.[13]

Crawling - Crawling is a process in which a web crawler creates indexes of all the words in a web-page, stores them, then follows all the hyperlinks and indexes on that page and again stores them.[14] It is the most popular technique for data acquisition and is also well-known for its easy operation based on prevalent Object-Orientated Programming Language (Java or Python etc.). And most important, social network companies (YouTube, Flicker, Facebook, Instagram and etc.) are friendly to crawling technique by providing public APIs [15]

Application

For Brands

Social media monitoring allows users to find insights into a brand's overall visibility on social media, measure the impact of campaigns, identify opportunities for engagement, assess competitor activity and share of voice, and be alerted to impending crises. It can also provide valuable information about emerging trends and what consumers and clients think about specific topics, brands or products.[16] This is the work of a cross-section of groups that include market researchers, PR staff, marketing teams, social engagement and community staff, agencies and sales teams. Several different providers have created tools to facilitate the monitoring of a variety of social media channels from blogging to internet video to internet forums. This allows companies to track what consumers are saying about their brands and actions. Companies can then react to these conversations and interact with consumers through social media platforms.[1]

For Government

Apart from the commercial application, social media monitoring is currently becoming a pervasive technique applied by public organization and government. Given that the monitoring is a tradition within the public sector, social media monitoring provides a real-time approach to face with the web monitoring challenges nowadays. Government comes to realize a need for strategies to cope with surprises from the rapid expansion of public issues. Sobkowicz [17] introduced a framework with three blocks of social media opinion tracking, simulating and forecasting. It includes: 1) real-time detection towards emotion, topic and opinion. 2) information flow modelling and agent-based simulation. 3) modeling of opinion networks.

The application of social media monitoring in Netherland was introduced by Bekkers.[18] Since 21st centuries, the public organizations in Netherland (such as Tax Agency and Education Ministry) start to use social media monitoring to obtain better insight into sentiments of target groups. On the one hand, the public sectors will be enabled to provide a timely and efficient answer to the public by using social media monitoring technique, but on the other hand, they also have to deal with the worries of some ethical problems regarding transparency or privacy.

Quantifying social media

Social media management software (SMMS) is an application program or software that facilitates an organisation's ability to successfully engage in social media across different communication channels. SMMS is used to monitor inbound and outbound conversations, support customer interaction, audit or document social marketing initiatives and evaluate the usefulness of a social media presence.[19]

It can be difficult to measure all social media conversation. Due to privacy settings and other issues, not all social media conversation can be found and reported by monitoring tools. However, whilst social media monitoring cannot give absolute figures, it can be extremely useful for identifying trends and for benchmarking, in addition to the uses mentioned above. These findings can, in turn, influence and shape future business decisions.

In order to access social media data (posts, Tweets, and meta-data) and to analyze and monitor social media, many companies use software technologies built for business.

Location-based

Most social media networks allow users to add a location to their posts (reference all of our feeds). The location can be classified as either 'at-the-location' or 'about-the-location'. "'At-the-location' services can be defined as services where location-based content is created at the geographic location. 'About-the-location' services can be defined as services which are referring to a particular location but the content is not necessarily created in this particular physical place."[20] The added information available from geotagged (link to Geotagging article) posts means that they can be displayed on a map. This means that a location can be used as the start of a social media search rather than a keyword or hashtag. This has major implications for disaster relief, event monitoring, safety and security professionals since a large portion of their job is related to tracking and monitoring specific locations.

Technologies used

Various monitoring platforms use different technologies for social media monitoring and measurement. These technology providers may connect to the API provided by social platforms that are created for 3rd party developers to develop their own applications and services that access data. Facebook's Graph API is one such API that social media monitoring solution products would connect to pull data from.[21] Technology companies may also get social data from a data reseller, such as DataSift or Gnip, which was acquired by Twitter. Some social media monitoring and analytics companies use calls to data providers each time an end-user develops a query. Others will also store and index social posts to offer historical data to their customers.

Additional monitoring companies use crawlers and spidering technology to find keyword reference. (See also: Semantic analysis, Natural language processing.) Basic implementation involves curating data from social media on a large scale and analyzing the results to make sense out of it.

See also

References

  1. 1 2 "Social Media Monitoring". Financial Times. Retrieved 30 October 2012.
  2. ↑ "Social media analytics". Wikipedia. 2017-10-29.
  3. ↑ Öztamur, Dilhan; Sarper Karakadılar, İbrahim (2014-09-15). "Exploring the Role of Social Media for SMEs: As a New Marketing Strategy Tool for the Firm Performance Perspective". Procedia - Social and Behavioral Sciences. 150: 511–520. doi:10.1016/j.sbspro.2014.09.067. ISSN 1877-0428.
  4. ↑ "Dey, L., Haque, S. M., Khurdiya, A., & Shroff, G. (2011, September). Acquiring competitive intelligence from social media" (PDF). In Proceedings of the 2011 joint workshop on multilingual OCR and analytics for noisy unstructured text data(p. 3). ACM.
  5. ↑ "What is social media metrics? - Definition from WhatIs.com". SearchContentManagement. Retrieved 2017-12-13.
  6. ↑ De, Shaunak; Maity, Abhishek; Goel, Vritti; Shitole, Sanjay; Bhattacharya, Avik (2017). "Predicting the popularity of instagram posts for a lifestyle magazine using deep learning". 2nd IEEEInternational Conference on Communication Systems, Computing and IT Applications (CSCITA): 174-177. doi:10.1109/CSCITA.2017.8066548.
  7. ↑ Murdough, C. (2009). "Social media measurement: It's not impossible" (PDF). Journal of Interactive Advertising. 10 (1): 94–99. doi:10.1080/15252019.2009.10722165.
  8. ↑ Krishnamurthy, Balachander (2009). "A measure of online social networks" (PDF). Proceeding COMSNETS'09 Proceedings of the First international conference on Communication Systems And networks: 190–199.
  9. ↑ Canali, Claudia; Colajanni, Colajanni; Lancellotti, Riccardo Lancellotti. "Data Acquisition in Social Networks: Issues and Proposals" (PDF).
  10. ↑ Wang, Wei (2011). "Network traffic monitoring, analysis and anomaly detection [Guest Editorial]". IEEE Network. 25: 6–7. doi:10.1109/mnet.2011.5772054.
  11. ↑ Andreolini, M. "Dynamic load balancing for network intrusion detection systems based on distributed architectures". s. In Proc. of 6th IEEE International Symposium on Network Computing and Applications.
  12. 1 2 Canali, Claudia; Colajanni, Colajanni; Lancellotti, Riccardo Lancellotti. "Data Acquisition in Social Networks: Issues and Proposals" (PDF).
  13. ↑ Batrinca, Bogdan; Treleaven, Philip C. (2015-02-01). "Social media analytics: a survey of techniques, tools and platforms". AI & SOCIETY. 30 (1): 89–116. doi:10.1007/s00146-014-0549-4. ISSN 0951-5666.
  14. ↑ Singh Ahuja, Mini; Singh Bal, Dr Jatinder; nica, Var (2014). "Web Crawler: Extracting the Web Data" (PDF). International Journal of Computer Trends and Technology. 13 (3): 132–137. doi:10.14445/22312803/ijctt-v13p128.
  15. ↑ Cha, M (2008). "Characterizing social cascades in Flickr". Proc. of the 1st Workshop on Online Social Networks (WOSP’08).
  16. ↑ "A New Approach to Measuring How Brands Are Portrayed On Social Media". NicheHunt. 9 June 2017. Retrieved 26 June 2017.
  17. ↑ Sobkowicz, Pawel; Kaschesky, Michael; Bouchard, Guillaume (October 2012). "Opinion mining in social media: Modeling, simulating, and forecasting political opinions in the web". Government Information Quarterly. 29 (4): Pages 470–479. doi:10.1016/j.giq.2012.06.005.
  18. ↑ Bekkers, VictorBekkers (October 2013, Pages). "Social media monitoring: Responsive governance in the shadow of surveillance?". Government Information Quarterly. 30 (4): 335–342. doi:10.1016/j.giq.2013.05.024. Check date values in: |date= (help)
  19. ↑ Owyang, J. (January 2012). "A Strategy for Managing Social Media Proliferation" (PDF). Altimeter Group.
  20. ↑ "Location-Based Marketing - Location-Based Social Media - Geoawesomeness".
  21. ↑ "Graph API". Retrieved 2015-05-14.
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