Essays about: "sociala medier nätverk"

Showing result 1 - 5 of 18 essays containing the words sociala medier nätverk.

1. 1. Designing Diverse Features to Reduce the Filter Bubble Effect on Social Media

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Ramya Kandula; [2023]
   Keywords : Filter bubbles; recommender systems; diversity; social media; filter bubblor; rekommenderande system; mångfald; sociala medier;

   Abstract : The filter bubble effect has been an active area of research that has been explored in various contexts within social media. Research on recommender system designs within filter bubbles has received a lot of attention, mainly due to its impact on the phenomena. READ MORE

3. 2. Impact of Central Nodes in Information Propagation over Graphs

   University essay from Lunds universitet/Matematisk statistik

   Author : Oskar Mellegård; [2023]
   Keywords : Mathematics and Statistics;

   Abstract : There are many systems which can be represented as graphs, to say the least the networks in which we communicate with each other. Thorough understanding of graph structures enables better predictions of the dynamics in real life networks, such as the spreading of a disease in a community or failure propagation in a system. READ MORE

4. 3. Exploring toxic lexicon similarity methods with the DRG framework on the toxic style transfer task

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Martin Iglesias; [2023]
   Keywords : Detoxifcation; Text style transfer; Deep learning; Transformers; Linguistics; Natural Language Processing; Hate speech; Text style-conditional generation; Large language model; Avgiftning; Överföring av textstil; Djupinlärning; Transformatorer; Lingvistik; Naturlig språkbehandling; Hatprat; Textstil - villkorlig generering; Stor språkmodell;

   Abstract : The topic of this thesis is the detoxification of language in social networks with a particular focus on style transfer techniques that combine deep learning and linguistic resources. In today’s digital landscape, social networks are rife with communication that can often be toxic, either intentionally or unintentionally. READ MORE

5. 4. RAISING A NEW COLLECTIVE VOICE THROUGH GREENFIELD UNION ORGANISING : The mobilisation and unionisation of workers and the establishment of a collective agreement at Foodora in Sweden

   University essay from Mälardalens högskola/Akademin för hälsa, vård och välfärd

   Author : Sophie Banasiak; [2021]
   Keywords : workforce fragmentation; food-delivery platforms; greenfield organising; unions; collective agreement; agency; structures; interactions; resources mobilisation; learning; strategy; institutional change; fragmentation du travail; plateformes de livraison de repas; implantation syndicale; syndicats; accord collectif; agence; structures; interactions; mobilisation des ressources; apprentissage; stratégie; changement institutionnel; fragmentering av arbetsstyrka; matleveransplattformar; greenfield-organisering; fackföreningar; kollektivavtal; mänskligt agentskap; strukturer; interaktioner; mobilisering av resurser; lärande; strategiskt handlande; institutionell förändring;

   Abstract : Following an actor-centred approach to institutional change, the aim of the study was to explore the process of ‘greenfield organising’ through which unions and collective bargaining structures are established in workplaces where there are none initially. A qualitative theory-oriented single case study, using some principles of the grounded theory, analysed the organising process and negotiations at Foodora in Sweden that resulted in a collective agreement. READ MORE

6. 5. Using Twitter Attribute Information to Predict Stock Prices

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Roderick Karlemstrand; Ebba Leckström; [2021]
   Keywords : Stock price prediction; Machine Learning; Deep Learning; Time series prediction; Twitter; Twitter attributes;

   Abstract : Being able to predict stock prices might be the unspoken wish of stock investors. Although stock prices are complicated to predict, there are many theories about what affects their movements, including interest rates, news and social media. With the help of Machine Learning, complex patterns in data can be identified beyond the human intellect. READ MORE