Event Study: Advanced Machine Learning and Statistical Technique for Analyzing Sustainability in Banking Stocks

Machine learning has grown in popularity in recent years as a method for evaluating financial text data, with promising results in stock price projection from financial news. Various research has looked at the relationship between news events and stock prices, but there is little evidence on how different sentiments (negative, neutral, and positive) of such events impact the performance of stocks or indices in comparison to benchmark indices. The goal of this paper is to analyze how a specific banking news event (such as a fraud or a bank merger) and other co-related news events (such as government policies or national elections), as well as the framing of both the news event and news-event sentiment, impair the formation of the respective bank’s stock and the banking index, i.e., Bank Nifty, in Indian stock markets over time. The task is achieved through three phases. In the first phase, we extract the banking and other co-related news events from the pool of financial news. The news events are further categorized into negative, positive, and neutral sentiments in the second phase. This study covers the third phase of our research work, where we analyze the impact of news events concerning sentiments or linguistics in the price movement of the respective bank’s stock, identified or recognized from these news events, against benchmark index Bank Nifty and the banking index against benchmark index Nifty50 for the short to long term. For the short term, we analyzed the movement of banking stock or index to benchmark index in terms of CARs (cumulative abnormal returns) surrounding the publication day (termed as D) of the news event in the event windows of (−1,D), (D,1), (−1,1), (D,5), (−5,−1), and (−5,5). For the long term, we analyzed the movement of banking stock or index to benchmark index in the event windows of (D,30), (−30,−1), (−30,30), (D,60), (−60,−1), and (−60,60). We explore the deep learning model, bidirectional encoder representations from transformers, and statistical method CAPM for this research.

False memories for true and false vaccination information form in line with pre-existing vaccine opinions

Misinformation has continually threatened efforts to control the COVID-19 pandemic, with vaccine misinformation now a key concern. False memories for misinformation can influence behavioural intentions, yet little is known about the factors affecting (false) memories for vaccine-related news items. Across two experiments (total N = 1,863), this paper explores the effects of pre-existing vaccine opinions on reported memories for true and false news items. In Study 1, participants (n = 1217) were exposed to fabricated pro- or anti-vaccine news items, and then asked if they have a memory of this news event having occurred. In Study 2, participants (n = 646) were exposed to true pro- or anti-vaccine news items. The results showed that news items were more likely to be remembered when they aligned with participants’ pre-existing vaccine beliefs. We conclude by encouraging researchers to consider the role of attitudinal bias when developing interventions to reduce susceptibility to misinformation.

Adapting the influences of publishers to perform news event detection

Online news outlets have the power to influence public policy issues. To understand the opinions of the people, many government departments check online news outlets to manually detect events that interest people. This process is time-consuming. To promptly respond to public expectations, this research proposes a framework for detecting news events that may interest government departments. This article proposes a method for finding event trigger words used to represent an event. The news media can be a critical participant in ‘agenda-setting’, which means that more widely discussed news is more attractive and critical than news that is less discussed. However, few studies have considered the influence of news media publishers from the ‘agenda setting’ perspective. Therefore, this study proposes an ‘agenda setting’-based filter to establish a high-impact news event detection model. The proposed framework identifies trigger words and utilises word embedding to find news event–related words. After that, an event detection model is designed to determine the events that are attractive to government departments. The experimental results show that purity increases from 0.666 when no extraction method is used to 0.809 when the extraction method in this study is used. The overall improvement trend shows significant improvement in event detection performance.

Characterizing financial markets from the event driven perspective

In this work we study how company co-occurrence in news events can be used to discover business links between them. We develop a methodology that is able to process raw textual data, embed it into a numerical form, and extract a meaningful network of connections. Each news event is considered as a node on the graph and we define the similarity between the two events as the cosine similarity between their vectors in the embedded space. Using this procedure, we contribute to the literature by successfully reconstructing business links between companies, which is usually a difficult task since the data on this topic is either outdated, incomplete or not widely available. We then demonstrate possible uses of this network in two forecasting applications. First, we show how the network can be used as an exogenous feature vector, which improves the prediction of the correlation between companies in the network. This correlation is determined from their realized variance as well as using a wide set of machine learning models for prediction. Second, we demonstrate the use of network for predicting future events with point processes. Our methodology can be applied on any series of events, where we have demonstrated and evaluated its applicability on news events and large market moves. For most of the tested algorithms the experimental results show an improvement in performance when including information from our graphs. More specifically, in certain sectors using Neural Networks shows improved performance by up to 50%.

ENGLISH TEACHERS’ STRATEGIES IN ASSESSING EIGHTH GRADERS' SPEAKING SKILL

The objective of the research are to find the strategies used by teachers in assessing speaking at SMPN 9 Kota Bengkulu. This research was quantitative approach. The subjects were twelve English lesson plans who use at eighth grade. The data were collected from documentation. The results showed that lesson plans were used five strategies from fourteen strategies in assessing speaking namely Oral Presentation, News Event, Roleplay, Discussion & Conversation, and Giving Instruction/Direction. In addition, online lesson plans used two strategies from fourteen strategies and offline lesson plans used four strategies from fourteen strategies. Further, the other nine strategies are not appeared in the class such as Repetition, Directed Response, Read Aloud, Sentence/Dialogue Completion, Question and Answer, Paraphrasing, Interview, Games and Story Telling. It can be happened because the lesson plans applied the strategies based on the students’ material, need, and condition in the meeting.

Fake News Detection Using Machine Learning

A huge quantity of knowledge is generated on social media platforms with varied social media formats. Once an event take place many folks discuss it on the web through social networking sites. They arrange or retrieve and discuss the news event and build it as a routine of their existence. However, terribly messy volume of report contains caused the user to face the matter of knowledge overloading throughout looking out and retrieving. Under level sources of knowledge expose individual to an outsize quantity of Fox News, rumours, Hawks is, conspiracy theories and dishonest news. This pretends news comes back from the information, misunderstanding or unreliable contents with the creditability supply. This makes it tough to discover whether to believe or not if the news may be pretend or a true one once the news data is received. The aim of this paper is to try to tackle the growing problems with pretend news, which has been continuously been a retardant by the widespread use of social media. During this paper, we have a tendency to use two classification models: Naïve Bayes and TF-IDF Vectorizer.

Deliberative Breakdowns in the Social Representation Process

This article examines breakdowns that occur when readers at partisan news websites attempt to understand a challenging news event. We conduct the work with the 2017 Alabama senate race as the empirical context marked by the nomination of Republican Roy Moore (a challenging news event for the left-leaning readers), and the story of his alleged sexual misconduct (a challenging news event for the right-leaning readers). To examine how readers attempt to understand these events, we scrape reader comments from two partisan news websites. Our analysis relies on and further elaborates the social representation theory and argumentation theory to identify obstacles that prevent successful progression of social representation processes: rhetorical, epistemological, and emotional breakdowns. The findings from our data reveal indicators of rhetorical breakdowns (greater occurrence of fallacious and non-argumentative reader comments) and epistemological breakdowns (greater use of doxastic comments) both tied to how challenging the news event is as well as indicators of emotional breakdowns (greater occurrence of attack posture) tied to the emotionally charged nature of the news event. We interpret the findings as a balancing act between protecting pre-existing representations and acknowledging the challenging news event. The indicators of potential breakdowns we find enhance our understanding of partisan political discourse viewed through the lens of social representation processes. The article discusses these contributions, including elaborations to social representation theory, and discusses implications of the work.

Humour as a strategy for news delivery: the case of Meduza

In this article, humour is viewed as a strategic resource for informing in media discourse. It is analyzed through the case of “Evening Meduza”, a Russian-language nightly newsletter, received via email or Telegram messenger. A media linguistics analysis of polycode hypermedia text is used to identify communicative linguistic means, contributing to a comic reinterpretation of news on the paratextual, intratextual and visual-illustrative level. News messages in the newsletter are created in the format of compressed “packagings” (a term borrowed from Chafe) with embedded links, following which an addressee goes to the page with source text or concomitant informational resources. Humour is analyzed in packagings as well as in whole text and paratext blocks. Humorous means are revealed in three vectors of analysis: empathy in packaging texts, paratextual focus interaction, and news visualization. The change of narrative perspectives in text packages allows the authors to shift the focus of contrast within a newspiece and create humorous content while showing empathy to readers with different presuppositional expectations. The author’s signature always includes a prepositive ironic addition (attribution) that highlights one of the issue’s news elements and forces the audience to reread the newsletter in order to understand the semantic relation. Subheadings create a comic contrast, focusing on individual parts of the reference content while preparing the reader to perceive the news of the day interconnectedly. A mandatory humorous component in the block “And – picture” was found to show the news event in a visual semiotic code using a demotivator style that expresses a pun.

Journalistic genre (Culture Coverage)

This variable describes the basic journalistic genres typically used in specialized cultural coverage. The fundamental distinction goes between fact-based objective-seeking genres, such as news and news feature, and opinionated articles based on subjective accounts, such as columns, essays, comments and reviews. In journalism, it is important to separate opinions from facts, and this is why subjective views are differentiated from ways of representation that are based on the strategic ritual of objectivity (Tuchman, 1972), i.e., presenting facts by referring to sources or simply describing them instead of exposing the journalists’ own opinions and feelings. Reviews present a specialist genre of their own, connected to the institution of criticism (Hohendahl, 1982). Reviewing – the evaluation of new cultural products on the market – underlies the assumption that only selected experts are allowed to write reviews (Chong, 2020). Newspapers are also constantly developing their means of presentation, which results in an increased number of different newspaper-specific and hybrid formats, both in print and online (see, e.g., Santos Silva, 2019). Being not only medium-specific, genres may also vary from one journalistic culture to another, which makes a nuanced cross-cultural comparison difficult and motivates a limited use of values. Field of application/theoretical foundation Journalistic genres constitute the epistemological ground on which cultural journalists and reviewers cover culture. Scholars have been interested in the shifts in cultural coverage that have occurred between descriptive, interpretative, and evaluative content (Widholm et al., 2019). Descriptive content is often regarded in professional terms as non-ambitious in culture, while the meaning-making subjective elements are preferred and conceived of as an indication of quality (proactive professional engagement rather than marketing of cultural events). In cultural coverage, it is yet often difficult to separate facts from evaluative accounts, as the description of products, phenomena, persons, and events often require that they are put into an evaluative frame. The selection of a genre is related to the production structures, as many reviews are written by freelancers outside the newsroom. The number and share of reviews are typically regarded as an indication of journalistic acknowledgement for expert knowledge, and also the volume of outsourced production, as a great majority of reviews are written by freelancer-based experts. A decreasing number of reviews is thus typically interpreted as a crisis of criticism (Elkins, 2003; Jaakkola, 2015). References/combination with other methods of data collection Journalistic genres are often studied in conjunction to the artistic genres (see variable “Forms of culture”). Some studies are only interested in tracing the number and volume of reviews. Sample operationalization The two basic journalistic genres are news and reviews. News coverage can be further broken down to news feature (phenomenon-led coverage also called reportage) and person-led feature (typically referred to as person portraits). Further, there are two typical opinionated genres, essays and columns, and many kinship genres such as analysis, (news) comment and preview, that can be separately identified or merged into one variable showing personal voicing of the author. Example study Jaakkola (2015) Information about Jaakkola, 2015 Author: Maarit Jaakkola Research question/research interest: Representation of the share of journalistic genres applied in covering culture on culture pages of daily newspapers across time, to expose the production structure Object of analysis: Articles/text items on culture pages of five major daily newspapers in Finland 1978–2008 (Aamulehti, Helsingin Sanomat, Kaleva, Savon Sanomat, Turun Sanomat) Timeframe of analysis: 1978–2008, consecutive sample of weeks 7 and 42 in five year intervals (1978, 1983, 1988, 1993, 1998, 2003, 2008) Info about variable Variable name/definition: Journalistic genre Unit of analysis: Article/text item Values: Journalistic genre Description 1. News Informative, fact-based article intended to deliver an objective account on an event 2. Review Opinionated, subjective article related to a new cultural product with an intention to evaluate it, written by a reviewer or critic 3. Person portrait/feature An informative article, typically interview-based, in which a person constitutes the topic 4. Reportage/feature An informative article intended to give account of the context of a news event or examine a phenomenon 5. Essay A longer opinionated, subjective article written by a journalist or reviewer to cover a phenomenon, process, state of the art or arts, etc. 6. Other commentary A short opinionated, subjective article written by a journalist (non-reviewer): a column, causerie, comment, preview or analysis, sometimes related to a news article 7. Other A text item not suited for any other category; e.g., a list, visualization, hybrid format, or similar Scale: nominal Intercoder reliability: Cohen's kappa > 0.76 (two coders) References Chong, P.K. (2020). Inside the critics‘ circle: Book reviewing in uncertain times. Princeton: Princeton University Press. Elkins, J. (2003). What happened to art criticism? Chicago: Prickly Paradigm Bristol University Presses. Hohendahl, P.U. (1982). Institution of criticism. Ithaca: Cornell University Press. Jaakkola, M. (2015). Witnesses of a cultural crisis: Representations of mediatic metaprocesses as professional metacriticism of arts journalism. International Journal of Cultural Studies, 18(5), 537–554. doi:10.1177/1367877913519308 Santos Silva, D. (2019). Digitally empowered: New patterns of sourcing and expertise in cultural journalism and criticism. Journalism Practice, 13(5), 592–601. doi: 10.1080/17512786.2018.1507682 Tuchman, G. (1972). Objectivity as strategic ritual: An examination of newsmen's notions of objectivity. American Journal of Sociology, 77(4), 660–679. doi:10.1086/225193 Widholm, A., Riegert, K., & Roosvall, A. (2019). Abundance or crisis? Transformations in the media ecology of Swedish cultural journalism over four decades. Journalism. Advance online publication August, 6. Journalism. doi:10.1177/1464884919866077

News as Entertainment Format

The informative value of news has often been the focus of mass communication research, but individuals do tune into the news for entertainment purposes. In addition, news organizations frequently add entertainment elements into news stories to increase audience interest. Considering both of these factors, theorizing about the entertainment processes (e.g., appreciation, enjoyment, and suspense) that occur during news consumption is necessary to understand audience behavior. This chapter investigates factors that influence entertainment processes during news consumption. Two entertainment theories in particular (affective disposition theory and the affective news extended model) are reviewed to understand how affective responses influence enjoyment of news. It organizes existing research on affective responses and entertainment processes into two categories focusing on news event characteristics (i.e., elements that journalists cannot change) and message design principles that journalists create or edit. Areas for future research are provided.