Event-Based Marketing: A Trendy and Emotional Way to Engage with the Public

Georgescu, Amalia; Avasilcăi, Silvia

doi:10.1007/978-981-15-1564-4_16

Cited by 3 publications

(1 citation statement)

References 7 publications

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“…Traditionally, trending correlates with the functioning of social networks, as well as psychological and anthropological mechanisms in the individual and society as a whole. It could be seen in the papers [41][42][43]…”

Section: Discussionmentioning

confidence: 98%

Framing as a tool of influencer marketing in the management of marketing communications and brand representation

Oklander¹,

Chaikovska²,

Shkeda³

2022

Economics of Development

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Topicality of the selected issue is due to the change in the orientation of brand communications in the information space from rational economic goals and values to behavioral economic ones, as well as the probability of incorrect decoding of the information message by the recipient of the information. The aim was to create a model of representative marketing communications transition from the formation of meanings to the formation of trends by using framing as an impact marketing tool. To accomplish the tasks set, the work uses the selection of general scientific and special methods and techniques of scientific research, such as the method of semantic, morphological, comparative and critical analysis, the ontology construction method, system-structural and functional approaches, simulation modeling, etc. The brand phenomenon is considered from the point of view of social constructivism, as a result of which seven principles of brand existence in the concept of communications with society have been identified. Two types of frameworks, which are used when building a narrative in the context of representative brand actions, have been substantiated theoretically. The methodology for using these frameworks is considered from the position of marketing, logical, communicative and social metrics included extensional and intensional equalities, as a result of which a model, that allows determining the transformation of brand communications into meanings or trends and its trendy potential, has been built. The following framing tools have been analyzed and adapted for marketing purposes: Overton Window, Hallin’s Spheres, Opinion Corridor, Spiral of Silence, Echo Chamber and Epistemic Bubble. Reframing is considered from the point of view of culture, namely the processes of inculturation. The difference of approaches has been revealed and a model of the transition of using framing tools from constructing meanings to constructing trends has been built. This model allows to minimize the problem of incorrect decoding of information during representative and communicative actions of the brand

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Section: Discussionmentioning

confidence: 98%

Framing as a tool of influencer marketing in the management of marketing communications and brand representation

Oklander¹,

Chaikovska²,

Shkeda³

2022

Economics of Development

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Emotion Extraction from Text Using Fuzzy-Deep Neural Network

Zaremarjal

Yiltas-Kaplan

Lazemi

2021

Lecture Notes in Networks and Systems

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Emotions are one of the most important and affective start points of our decisions in daily life. People express their emotions, consciously or unconsciously, in their behaviors, like speech, facial expressions, textual content, and so on, whether it be in blogs, reviews, or on social media. Due to the rapid growth in textual social media to link people, the emotion extraction from textual data has attracted a lot of attention. This paper performs the sentence-level discrete emotion extraction from text by using Fuzzy Neural Networks (FNN) and Deep Recurrent Neural Networks (DRNN). Much work has been presented to extracting emotion from textual data with precise and constant boundaries, but little of it has considered the inherent uncertainty in natural language. In other words, the high ambiguity of emotion in text data makes an emotionally sentence express multiple emotions at the same time. To deal with this uncertainty we use a Neuro Neural Network (NNN). But from another point of view, by increasing the number of inputs, the number of parameters in NNN growth exponentially. To this end, we extract a low-dimensional semantic representation of input sentence by using a Bi-directional Long Short-Term Memory (Bi-LSTM). Our goal is to achieve better performance with combining the advantages of deep learning in high-level semantic feature extraction to ambiguity handling and the capabilities of fuzzy logic with fuzzy membership degrees to uncertainty handling. Experiments are conducted on the SemEval2007-Task14 dataset that contains 1250 annotated texts with Ekman's basic emotions. The obtained results indicate that our proposed method outperforms the previous methods.

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MDER: Multi-Dimensional Event Recommendation in Social Media Context

Troudi

Ghorbel

Zayani

et al. 2020

The Computer Journal

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Events represent a tipping point that affects users’ opinions and vary depending upon their popularity from local to international. Indeed, social media offer users platforms to express their opinions and commitments to events that attract them. However, owing to the volume of data, users are encountering a difficulty to accede to the preferred events according to their features that are stored in their social network profiles. To surmount this limitation, multiple event recommendation systems appeared. Nevertheless, these systems use a limited number of event dimensions and user’s features. Besides, they consider users’ features stored in a single user’s profile and disregard the semantic concept. In this research, an approach for multi-dimensional event recommendation is set forward to recommend events to users resting on several event dimensions (engagement, location, topic, time and popularity) and some user’s features (demographic data, position and user’s/friend’s interests) stored in multi-user’s profiles by considering the semantic relationships between user’s features, specifically user’s interests. The performance of our approach was assessed using error rate measurements (mean absolute error, root mean squared error and cross-validation). Experiment that results on real-world event data sets confirmed that our approach recommends events that fit the user more than the previous approaches with the lowest error rate values.

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Event-Based Marketing: A Trendy and Emotional Way to Engage with the Public

Cited by 3 publications

References 7 publications

Framing as a tool of influencer marketing in the management of marketing communications and brand representation

Framing as a tool of influencer marketing in the management of marketing communications and brand representation

Emotion Extraction from Text Using Fuzzy-Deep Neural Network

MDER: Multi-Dimensional Event Recommendation in Social Media Context

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