title: Network effect and investor’s perceptions: An empirical investigation

authors: Feroz, Noushad Khan

subjects: Financial information

abstract: Investors’ perceptions, and their understanding related to an investment, are paramount to decision-making in economic and investment settings. Social media is increasingly playing a vital role in influencing investors’ perceptions and investors’ decisions in the financial arena. Social media is a comfortable and easy tool to use. That’s why it has just become a fundamental part of online news sharing and information distribution.

In the first study of this thesis, a network structure is constructed and built social ties circle based on the frequency of communication of investors within the network, and the network size of the investors to develop a comprehensive measurement scale for the social network index. Our findings indicate that the acquisition of information in the social network of investors depends on different components or factors. A significant factor in the network index is the network degree (network connectivity). It implies that network members with higher degrees or connections acquire vast amounts of information. Likewise, investors with larger networks receive enormous amounts of information, notably "following," which is the principal component in terms of network size. As a result, network size appears as the network index's second biggest factor. The smaller contribution comes from social tie circles. However, collectively, all these factors represent the social network index.

In the second study, we argue that the impact of financial information and news on investors’ perceptions is moderated by network factors such as network structure, social ties, and network size of the network. The impact of information on an individual’s perception is also called a social network or network effect. To tackle the moderating role of these network factors, we employed PLS-SEM as a statistical technique. The findings of this study indicate that network connectivity and social ties are crucial for the acquisition of information within the network. The findings of the study also show that network connectivity and social ties circle plays a central role in determining the impact of financial information. Our study further indicates that the impact of financial information and news on investors’ perceptions depends on their theme.

In the third essay of this thesis, we investigate how investors’ perceptions and preferences in terms of trading are influenced by their cultural background and network factors. In this study, we considered the moderating role of network factors in a cross-cultural context. The main subjects of our research datasets are investors who buy and sell shares and/or stocks of companies listed on the stock exchanges of New Zealand and South Korea. In this study, we examined data from 214 retail investors from the New Zealand Stock Exchange (NZX) and South Korea. In comparison to non-kiwi investors, the study's findings show that network factors have a major impact on how information is disseminated among Kiwi investors. The results of this study also demonstrate that network factors' effects differ across cultures and countries.

To conclude, Twitter is a major social media platform that helps investors to connect with their counterparts and obtain financial information through back-and-forth interactions. However, access to information on social networks depends on network structure (network connectivity), social ties circle (family, friends, and colleagues), and network size (number of contact or followers and followings). Twitter also enables prompt dissemination of financial news and information, which can substantially impact investors’ perceptions. However, the impact of information on investors’ perceptions varied cross-culture because of varied network factors.

text: Network effect and investor’s perceptions: An empirical investigation Investors’ perceptions, and their understanding related to an investment, are paramount to decision-making in economic and investment settings. Social media is increasingly playing a vital role in influencing investors’ perceptions and investors’ decisions in the financial arena. Social media is a comfortable and easy tool to use. That’s why it has just become a fundamental part of online news sharing and information distribution.

In the first study of this thesis, a network structure is constructed and built social ties circle based on the frequency of communication of investors within the network, and the network size of the investors to develop a comprehensive measurement scale for the social network index. Our findings indicate that the acquisition of information in the social network of investors depends on different components or factors. A significant factor in the network index is the network degree (network connectivity). It implies that network members with higher degrees or connections acquire vast amounts of information. Likewise, investors with larger networks receive enormous amounts of information, notably "following," which is the principal component in terms of network size. As a result, network size appears as the network index's second biggest factor. The smaller contribution comes from social tie circles. However, collectively, all these factors represent the social network index.

In the second study, we argue that the impact of financial information and news on investors’ perceptions is moderated by network factors such as network structure, social ties, and network size of the network. The impact of information on an individual’s perception is also called a social network or network effect. To tackle the moderating role of these network factors, we employed PLS-SEM as a statistical technique. The findings of this study indicate that network connectivity and social ties are crucial for the acquisition of information within the network. The findings of the study also show that network connectivity and social ties circle plays a central role in determining the impact of financial information. Our study further indicates that the impact of financial information and news on investors’ perceptions depends on their theme.

In the third essay of this thesis, we investigate how investors’ perceptions and preferences in terms of trading are influenced by their cultural background and network factors. In this study, we considered the moderating role of network factors in a cross-cultural context. The main subjects of our research datasets are investors who buy and sell shares and/or stocks of companies listed on the stock exchanges of New Zealand and South Korea. In this study, we examined data from 214 retail investors from the New Zealand Stock Exchange (NZX) and South Korea. In comparison to non-kiwi investors, the study's findings show that network factors have a major impact on how information is disseminated among Kiwi investors. The results of this study also demonstrate that network factors' effects differ across cultures and countries.

To conclude, Twitter is a major social media platform that helps investors to connect with their counterparts and obtain financial information through back-and-forth interactions. However, access to information on social networks depends on network structure (network connectivity), social ties circle (family, friends, and colleagues), and network size (number of contact or followers and followings). Twitter also enables prompt dissemination of financial news and information, which can substantially impact investors’ perceptions. However, the impact of information on investors’ perceptions varied cross-culture because of varied network factors.

year: 2023

title: Cross-Needle Analog Meter to Monitor Charge
Time for Lithium-Ion Single Cell

authors: Scott, Jonathan B.

abstract: This manuscript describes a novel cross-needle analogmeter whose scale reads out voltage, current, and time remaining to reach full charge. The design is inspired by cross-needle Standing Wave Ratio(SWR) meters that read forward and reverse power. Voltage is displayed on an offset-zero linear scale, and current on a logarithmic scale from 1 mA to 10 A. Thisleads to a wide range of perceptible charge times and pleasantcharge-time contour lines. The prototype is implemented on a single PCB using a cheap PIC micro controller. It is scaled formonitoring a single 18650 lithium cell charged by a small solarpanel. The Novel contribution of this paper is the use of a crossneedleanalog meter with a third scale to measure time remaining to fully charge a Lithium-Ion single cell battery.

text: Cross-Needle Analog Meter to Monitor Charge
Time for Lithium-Ion Single Cell This manuscript describes a novel cross-needle analogmeter whose scale reads out voltage, current, and time remaining to reach full charge. The design is inspired by cross-needle Standing Wave Ratio(SWR) meters that read forward and reverse power. Voltage is displayed on an offset-zero linear scale, and current on a logarithmic scale from 1 mA to 10 A. Thisleads to a wide range of perceptible charge times and pleasantcharge-time contour lines. The prototype is implemented on a single PCB using a cheap PIC micro controller. It is scaled formonitoring a single 18650 lithium cell charged by a small solarpanel. The Novel contribution of this paper is the use of a crossneedleanalog meter with a third scale to measure time remaining to fully charge a Lithium-Ion single cell battery.

year: 2017

title: Diacritic Restoration and the Development of a Part-of-Speech Tagset for the Māori Language

authors: Cocks, John

subjects: Māori

abstract: This thesis investigates two fundamental problems in natural language processing: diacritic restoration and part-of-speech tagging. Over the past three decades, statistical approaches to diacritic restoration and part-of-speech tagging have grown in interest as a consequence of the increasing availability of manually annotated training data in major languages such as English and French. However, these approaches are not practical for most minority languages, where appropriate training data is either non-existent or not publically available. Furthermore, before developing a part-of-speech tagging system, a suitable tagset is required for that language. In this thesis, we make the following contributions to bridge this gap:

Firstly, we propose a method for diacritic restoration based on naive Bayes classifiers that act at word-level. Classifications are based on a rich set of features, extracted automatically from training data in the form of diacritically marked text. This method requires no additional resources, which makes it language independent. The algorithm was evaluated on one language, namely Māori, and an accuracy exceeding 99% was observed.

Secondly, we present our work on creating one of the necessary resources for the development of a part-of-speech tagging system in Māori, that of a suitable tagset. The tagset described was developed in accordance with the EAGLES guidelines for morphosyntactic annotation of corpora, and was the result of in-depth analysis of the Māori grammar.

text: Diacritic Restoration and the Development of a Part-of-Speech Tagset for the Māori Language This thesis investigates two fundamental problems in natural language processing: diacritic restoration and part-of-speech tagging. Over the past three decades, statistical approaches to diacritic restoration and part-of-speech tagging have grown in interest as a consequence of the increasing availability of manually annotated training data in major languages such as English and French. However, these approaches are not practical for most minority languages, where appropriate training data is either non-existent or not publically available. Furthermore, before developing a part-of-speech tagging system, a suitable tagset is required for that language. In this thesis, we make the following contributions to bridge this gap:

Firstly, we propose a method for diacritic restoration based on naive Bayes classifiers that act at word-level. Classifications are based on a rich set of features, extracted automatically from training data in the form of diacritically marked text. This method requires no additional resources, which makes it language independent. The algorithm was evaluated on one language, namely Māori, and an accuracy exceeding 99% was observed.

Secondly, we present our work on creating one of the necessary resources for the development of a part-of-speech tagging system in Māori, that of a suitable tagset. The tagset described was developed in accordance with the EAGLES guidelines for morphosyntactic annotation of corpora, and was the result of in-depth analysis of the Māori grammar.

year: 2012