class: center, middle, inverse, title-slide .title[ # Learning Social Media Analytics ] .subtitle[ ## Lecture 1 Course introduction ] .author[ ### Luka Sikic PhD ] .institute[ ### Fakultet hrvatskih studija ] .date[ ### (updated: 2023-03-07) ] --- # STRUCTURE <br> <br> <br> <br> - General course information <br> <br> - Objectives of the course <br> <br> - Course Literature <br> <br> - Data and resources <br> <br> --- layout: true # GENERAL COURSE INFORMATION --- <br> #### What is this all about? <br> <br> <br> - understand social media landscape and trends <br> <br> - focus is on methods and techniques for social media analysis <br> <br> - state of the art tools for social media analysis <br> <br> - independently interpret, analyse or/and develop social media strategy --- <br> #### How do we do that? <br> <br> <br> - R and Python will be be used for the purposes of demonstrating methods <br> <br> - prior knowledge od the programming language syntax is not necessery <br> <br> - learning some of the basic syntax is warmly recommended <br> <br> - we can dedicate one lecture to syntax --- <br> #### In the background! <br> <br> - *data science* techniques in focus <br> <br> - working with databases (*SQL*,*Google Big Querry*) <br> <br> - web data (*web scraping*, *API*) <br> <br> - data manipulation and cleaning (*tidyverse*, *pandas*, *data.table*) <br> <br> - IT ollaboration and code sharing (*Git*, *GitHub*) and open source reporting (*RMarkdown*) <br> <br> - *computational social science* paradigm --- <br> #### Syllabus <br> <br> <br> - unofficial [syllab](https://raw.githack.com/lusiki/Learning-Social-Media-Analytics/main/syllab/syllab.html) (please follow up for updates); also as [.pdf](https://github.com/lusiki/Learning-Social-Media-Analytics/blob/main/syllab/syllab.pdf). <br> <br> - offiical syllab on [English](https://github.com/lusiki/Learning-Social-Media-Analytics/blob/main/syllab/Learning%20social%20media%20analytics.docx) and [Croatian](https://github.com/lusiki/Learning-Social-Media-Analytics/blob/main/syllab/Analitika%20dru%C5%A1tvenih%20medija.docx) --- layout: true # OBJECTIVES OF THE COURSE --- <br> <br> <br> - Catching up with the current state and trends in the social media space <br> <br> - IT infrastructure (Big Data) of social media platforms <br> <br> - Relevant topics in social media research and business <br> <br> - Tools, methodology and results in social media analytics <br> <br> - Independent social media research --- layout: true # COURSE LITERATURE --- <br> #### Books <br> <br> - [Mining the Social Web](https://www.webpages.uidaho.edu/~stevel/504/mining-the-social-web-2nd-edition.pdf) <br> <br> - [Learning Social Media Analytics with R](https://www.packtpub.com/product/learning-social-media-analytics-with-r/9781787127524) <br> <br> - [Mastering Social Media Mining with Python](https://www.packtpub.com/product/mastering-social-media-mining-with-python/9781783552016) <br> <br> - [Social Media Data Mining and Analytics](https://www.wiley.com/en-us/Social+Media+Data+Mining+and+Analytics-p-9781118824856) <br> <br> - [Social Media Analytics Strategy](https://www.apress.com/us/book/9781484231012) --- <br> #### Academic literature <br> <br> - [International Conference on Web and Social Media](https://ojs.aaai.org/index.php/ICWSM/issue/archive) <br> <br> - [Social Media + Society](https://journals.sagepub.com/home/sms) <br> <br> - [Information, Communication & Society](https://www.tandfonline.com/journals/rics20) <br> <br> - Optionally you can pick another journal to follow, check the [list](https://lusiki.github.io/Learning-Social-Media-Analytics/resources.html) --- layout: true # DATA AND RESOURCES --- <br> #### Data <br> <br> - There are numerous social media data sources <br> <br> - We will be working with Croatian data so please thoughly check [Mediatoolkit](https://www.mediatoolkit.com/) (alternatives are [presscut](https://www1.presscut.hr/en/), [pressclipping](https://www.pressclipping.hr/)) <br> <br> - Data samples are provided in the repo <br> <br> - These data sources are equally inconvenient (expensive and partitial) <br> <br> - Serious solution requires your own database complilation --- <br> #### Resources <br> <br> - There are countless social media resources <br> <br> - Please check my [curated list](https://lusiki.github.io/Learning-Social-Media-Analytics/resources.html) <br> <br> - Consider adding to it (maybe as a student project) --- class: inverse, middle layout:false # Thank you for your attention!